Advancing the science of integrating multiple interventions by blending and bundling

Abstract

Cancer prevention and control research has produced a variety of effective interventions over the years, though most are single disease focused. To meet the Cancer MoonshotSM goal to reduce the cancer death rate by 50% by 2047, it may be necessary to overcome the limitations of siloed interventions that do not meet people’s multiple needs and limitations in system capacity to deliver the increasing number of interventions in parallel. In this article we propose integrating multiple evidence-based interventions as a potential solution. We define two types of integrated interventions, blended and bundled, and provide examples to illustrate each. We then offer a schematic and outline considerations for how to assemble blended or bundled interventions including looking at the intervention need or opportunity along the cancer continuum as well as co-occurring behaviors or motivations. We also discuss delivery workflow integration considerations including social-ecological level(s), context or setting, implementer, and intended beneficiary. Finally in assembling integrated interventions, we encourage consideration of practice-based expertise and community/patient input. After assembly, we share thoughts related to implementation and evaluation of blended or bundled interventions. To conclude the article, we present multiple research opportunities in this space. With swift progress on these research directions, cancer prevention and control interventionists and implementation scientists can contribute to achieving the promise of the reignited Cancer MoonshotSM.

Syndemic Geographic Patterns of Cancer Types in a Health Deprived Area of England: a new Paradigm for Public Health Cancer Interventions?

“…This is likely attributable to the fact that these cancers share risk factors such as alcohol consumption, ethnicity, obesity and smoking, but also infectious diseases 6 . This reinforces the ‘integrating intervention’ paradigm, where interventions are designed to reduce and eliminate multiple cancers instead of tackling individual cancers especially when risk factors are identified (Subramanian et al, 2022, Villalobos and Chambers, 2023). The latter was a designed-in goal of this research, which aimed not only to select the risk factors for each cancer type, but also to find areas with correlated residuals (or in other words residual patterns of co-occurrence)(Pollock et al, 2014) which are indicative of the presence of factors or biological processes associated to both cancers, but not considered in the model (Jahan et al, 2020).…”