A tool to measure complexity in public health interventions

Background and objectivePublic health interventions are targeted to a diverse population, composed of multiple components, mostly context dependent and therefore they are often regarded as complex. The complex nature of the public health interventions discourages the use of conventional Meta-analytic techniques and acts as a hurdle to combine the findings of studies conducted across different locations. Measuring complexity of different studies and adjusting for these complexities during Meta-analysis would be an appropriate method to address this problem and obtains the pooled estimate. Hence this study was conducted with an objective of developing a tool for quantifying the complexities in public health intervention studies.MethodologyWith the help of a large number of published public health interventions, a checklist was prepared for compiling the instrument. The checklist was obtained for all the domains namely population, intervention, context and outcome. This was further debated and cross checked with experts to form the final list. Items in the final list were appropriately scored for each domain based on long discussions, debates and expert meetings and obtained the tool. The reliability of the tool was assessed by two raters independently scoring the same studies with the developed tool and computing the Intra-class Correlation Coefficient (ICC). Further the tool was applied to a number of studies to measure domain specific and overall complexities.Results and conclusionThe overall ICC of the tool was found to be 0.840 and ICC for population, intervention and outcome was found to be good (0.855, 0.859 and 0.916 respectively), whereas ICC for context was found to be low (0.381). The tool was applied to measure the complexities of population, intervention, context and outcome of 26 Public health intervention publications. The tool has a good scope for application in Meta-analysis of public health systematic reviews.