Development of an overarching framework for anticipating and assessing adverse and other unintended consequences of public health interventions (CONSEQUENT): a best-fit framework synthesis

Abstract

Introduction Despite the best intentions and intended beneficial outcomes, public health (PH) interventions can have adverse effects and other unintended consequences (AUCs). AUCs are rarely systematically examined when developing, evaluating or implementing PH interventions. We, therefore, used a multipronged, evidence-based approach to develop a framework to support researchers and decision-makers in anticipating and assessing AUCs of PH interventions.Methods We employed the ‘best-fit’ synthesis approach, starting with an a priori framework and iteratively revising this based on systematically identified evidence. The a priori framework was designed using key elements of the WHO-INTEGRATE framework and the Behaviour Change Wheel, to root it in global health norms and values, established mechanisms of PH interventions and a complexity perspective. The a priori framework was advanced based on theoretical and conceptual publications and systematic reviews on the topic of AUCs in PH. Thematic analysis was used to revise the framework and identify new themes. To test the framework, it was coded against four systematic reviews of AUCs of PH interventions.Results The Cosequences of Public Health Interventions (CONSEQUENT) framework includes two components: the first focuses on AUCs and serves to categorise them; the second (supplementary) component highlights the mechanisms through which AUCs may arise. The first component comprises eight domains of consequences: health, health system, human rights, acceptability and adherence, equality, and equity, social and institutional, economic and resources, and the environment.Conclusion The CONSEQUENT framework is intended to facilitate classification and conceptualisation of AUCs of PH interventions during their development or evaluation to support evidence-informed decision-making.