Abstract

This article has called past studies into question as they relate to describing and explaining the impact of information on policy-making. More specifically, it attempts to empirically investigate the causality of the factors involved in the impact of information on governmental decision-making. Based on an integrated conceptual framework for when and how information helps to make policy decisions, a path model (or a covariance structure model without latent variables) is built and tested against the data in two areas of mental health policy (i.e., service provision and financing). Findings of the study demonstrate that how and when information influences governmental decision-making is directly and indirectly affected by a variety of factors and their linkages, not dominated by one set of factors (e.g., trustworthiness of information source or format of reports) defined by a single perspective (e.g., the organizational interest or the communications perspective). The most important paths in the model are those between factors related to information (e.g., the amount of information received or its use) and the impact of information on policy-making. Interestingly, these factors also play a major role in linking other variables (e.g., demographics or decision makers’ distrust of information) to the impact of information on policy-making. Furthermore, the general pattern of the findings indicates that policy areas make a difference in accounting for the impact of information on policy-making. Overall, the single most important lesson is that past perspectives are not alternative or competing tools for understanding the phenomena, and, thus, the theoretical and/or empirical task of explaining when and why information affects policy-making is equivalent to explaining why a certain set of factors is not appropriate or appropriate for a particular context and to identifying such a context.