Evaluating injury prevention interventions.

wo papers, one from Sweden 1 and one from Australia, 2 in this issue describe evaluations of injury prevention interventions. In both, multimo-dal community based interventions were implemented in defined geographic areas. Both face the challenges of evaluating a complex intervention, delivered in a " real world " setting and without a randomized trial structure. Evaluating injury prevention efforts is vital to reduce the rising toll of mortality , morbidity, and economic losses arising from injuries, not only to identify effective prevention measures but also to shift resources from what does not work to what does. For these reasons, it is essential that evaluation be of the highest methodological standard possible. In most scientific inquiry, the investigator approaches a problem with a hunch or more formally, a hypothesis. In the injury prevention field, most of us are believers, of varying degrees of fervency, that injuries can be prevented and that interventions to do so can be implemented. These beliefs motivate evaluation but the evaluation itself can rarely if ever provide the positivist proof that the intervention reduced rates or severity of injuries. Ensuring that the evaluation's conclusions are able to withstand alternative explanations is critical. For this reason, evaluations ideally begin from a premise of no effect and seek to demonstrate that this is not so. This distinction is important , in part because the falsification of the hypothesis of " no effect " is at the heart of commonly used frequentist statistical tests such as those reported in both papers. Two additional elements are also important: clarification of the contrast and the need for efforts to rule out alternative explanations of the observed effects. CLARIFYING THE CONTRAST In a randomized study, the contrast is clear. Some subjects (individuals or communities) receive one intervention and the others do not. In pharmaceutical trials, placebos further clarify the contrast by theoretically nullifying the difference between taking a pill and not taking a pill, since all participants take something and typically are unaware of whether it is active agent or placebo (blinding). The interventions reported in this issue were not randomized to some communities and even if they were, providing a " placebo " counterpart to the communities not receiving the intervention would be difficult. Nevertheless, offsetting some of the differences between the communities being compared is possible using analytic tools. On the positive side, Ozanne-Smith and colleagues report using age standardization to …