Health promotion and prevention actions are challenging interventions in complex social systems. Outcomes are aimed at different levels of intervention with different time perspectives. However, the complexity of social systems means that the potential to plan such outcomes is limited. Chains of effects are varied and dynamic, characterized by a great variety of interaction and back loops. Unintentionally, small causes can have great effects; multiple side effects are the norm rather than the exception. Simple and direct correlations of cause and effect are rarely observed and then occur in short-term and strictly delimited interventions only. Given that longer lasting and more complex interventions are open to many influences, hypothetical correlations of cause and effect quickly loose significance. Thus, one cannot really determine the contribution that one specific intervention has made on any observed effect.
Outcome models are one of many methods to deal with this complexity. They propose to prioritize and to classify resources, measures and (planned)effects of health promotion and prevention, they also illustrate chains of effects. In current outcome models, effects achieved at different times and on different levels of a project or a programme are neatly arranged and an attempt is made to illustrate the many intermediate steps and the many spheres of influence that are encountered in the process of reaching the distant goal which is ‘health’. But given the complexity mentioned above, prudence and humility are needed: the whole complex nature of reality cannot truly be captured by even the most sophisticated outcome model – models can only depict a snippet of reality that is deemed to be relevant (reduction of complexity). Outcome models only point to possible correlations of effects, but cannot make predictions with a high probability. Furthermore, it must not be forgotten that outcome models are highly context dependent - they cannot simply be applied to different contexts but must be reflected and adapted. Once elaborated, they are not static but must equally be reflected and adapted to the continuously changing dynamic of social systems.
Such models are particularly useful for evaluative planning. With the basic outline of a project or a programme in place, the coherence of the planning can be systematically pondered. On which trajectories of a health problem is the concept based (effect logic of the problem)? Does the planned project promise to give adequate answers to the particular problem (effect logic of the project)? Used in such a way, outcome models such as the SMOC (Swiss model of Outcome Classifications) are versatile instruments for reflection and quality development; they are especially useful for rapidly identifying the essential elements within complex systems. Outcome models challenge us to think carefully about effects in complex systems. They stop us from rash assumptions of simplistic chains of cause and effect.
Outcome models are particularly useful if they are developed and used by more than one person. When used by a project team – and ideally in association with other stakeholders and experts – such a model will help to bring to light the expertise of the different team members as well as expose and align different points of view and interests. This kind of participatory approach greatly advances a common understanding of the system in which interventions are being planned, a common understanding of the problem and a commonly agreed strategy of intervention.