Develop population-based interventions to motivate health-promoting behaviors
Evidence-based.
Developing effective interventions is one thing; developing an intervention that is effective in the population as a whole is quite another. The process is comparable to the work of engineers in the construction of a machine. From conceptualization to the analysis of the mechanisms of action, from test series to the first use. We take a similar approach to the development of interventions. The ORBIT model has been developed by a working group at the National Institutes of Health. ORBIT describes an iterative process for translating empirical findings into interventions for the prevention and treatment of chronic diseases. The principle: The intervention development occurs in study phases that are comparable to those in drug development. This allows us to see what works well and where improvements are needed. Only when we determine that the milestones of a particular phase have been reached, the study of the subsequent phase begins. This evidence-based approach intends to maximize the likelihood that the intervention will produce meaningful effects in the population and pass rigorous efficacy testing in a randomized controlled trial.
Individualized.
Individualization takes into account the characteristics of the individual while addressing an entire population. The goal is to develop personalized intervention programs with the right messages for the individual person. To this end, we use health psychological theories and models of behavior change from which individualized motivational strategies with high personal relevance can be derived.
Computer-based.
Population-wide application requires interventions that can address people individually and motivate them to change their behavior at low costs. Interventions that meet these requirements are expert systems. An expert system is a computer program that automatically interacts with a person to produce feedback tailored to that person. Specifically, the expert system interprets information about the individual, such as his or her motivation to change behavior, by comparing it to an empirical database on the same variables from population samples and generates individualized feedback based on if-then rules. In addition, after two or more interactions with a person, the expert system can make interpretations of individual changes over time, e.g., progress in motivational development.
