![]() In the context of policy evaluation, a pre-specified logic model allows researchers to test existing hypotheses about the effect of policy, in some cases using prospective data that are collected specifically for the purposes of evaluation. Ideally, programme theories should be articulated prior to the implementation of public health interventions, as part of the justification for their introduction, thus providing an a priori judgement, based on well-considered evidence, of how and in whom they will work. 7, 8 Programme theory and logic models can be a valuable tool in intervention planning and implementation as well as in evaluation. 1) others may seek to capture more complex pathways, such as non-linear pathways or multiple causal strands. Logic models are most frequently simple, linear models ( Fig. The programme theory can be represented visually in a logic model, which shows the anticipated causal pathway of an intervention and the populations expected to be affected. One way of mitigating the above challenges is to articulate the programme theory, which describes how each policy is likely to work and in whom. Despite these challenges, studies which evaluate natural experiments can make a contribution to the evidence base for public health. For example, in England, tobacco control policies have often been implemented close together-such as the smoking ban in public places and the increase in the minimum age of purchase for tobacco products in 2007-and standardized tobacco packaging and the European Union Tobacco Products Directive, which also made changes to the appearance of tobacco products in 2016. 2 This is a particular problem in settings where several policies are implemented in a short period of time. 2 Others, such as longitudinal studies, interrupted times series and difference-in-difference analysis, have greater internal validity but face challenges in disentangling policy effects from secular trends and other factors which contribute to changes in relevant outcomes. 3 Some, such as cross-sectional designs, have particularly low internal validity. The evaluation of these ‘natural experiments’, therefore, often involves in observational designs and frequently relying on routinely collected data such as health service records or population surveys. ![]() 2 Furthermore, researchers may not have the opportunity to design studies and collect relevant data prospectively. This requires the identification of important outcome measures and appropriately designed analyses to measure policy impact.Ī key challenge in this type of policy evaluation is the attribution of causality-does the policy cause a change in health outcomes, or is the change attributable to something else? 1 Population-level policy changes cannot usually be evaluated using randomized-controlled trials, because governments, rather than researchers, control their implementation. ![]() The maintenance, improvement and expansion of these policies depend on post-implementation evaluation of their effectiveness. Large-scale public policy interventions, such as tobacco tax increases and regulation of advertising for unhealthy commodities, are regularly implemented with a view to improving public health. Evaluation, logic models, public health policy, tobacco control Introduction ![]()
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