How to design a complex behaviour change intervention: experiences from a nutrition-sensitive agriculture trial in rural India

Abstract

Many public health interventions aim to promote healthful behaviours, with varying degrees of success. With a lack of existing empirical evidence on the optimal number or combination of behaviours to promote to achieve a given health outcome, a key challenge in intervention design lies in deciding what behaviours to prioritise, and how best to promote them. We describe how key behaviours were selected and promoted within a multisectoral nutrition-sensitive agriculture intervention that aimed to address maternal and child undernutrition in rural India. First, we formulated a Theory of Change, which outlined our hypothesised impact pathways. To do this, we used the following inputs: existing conceptual frameworks, published empirical evidence, a feasibility study, formative research and the intervention team's local knowledge. Then, we selected specific behaviours to address within each impact pathway, based on our formative research, behaviour change models, local knowledge and community feedback. As the intervention progressed, we mapped each of the behaviours against our impact pathways and the transtheoretical model of behaviour change, to monitor the balance of behaviours across pathways and along stages of behaviour change. By collectively agreeing on definitions of complex concepts and hypothesised impact pathways, implementing partners were able to communicate clearly between each other and with intervention participants. Our intervention was iteratively informed by continuous review, by monitoring implementation against targets and by integrating community feedback. Impact and process evaluations will reveal whether these approaches are effective for improving maternal and child nutrition, and what the effects are on each hypothesised impact pathway.

Keywords: Cluster randomised trial; child health; maternal health; nutrition.

Figure 1

Overview of Upscaling Participatory Videos and Action for Agriculture and Nutrition (UPAVAN) interventions, taken from Kadiyala et al. NSA, nutrition-sensitive agriculture; PLA, Participatory Learning and Action.

Figure 2

Unpacking the possible pathways, behaviours and capabilities, opportunities and motivations that Upscaling Participatory Videos and Action for Agriculture and Nutrition (UPAVAN) could prioritise.

Figure 3

Key stages in the development and prioritisation of Upscaling Participatory Videos and Action for Agriculture and Nutrition (UPAVAN) interventions. PLA, Participatory Learning and Action; VARRAT, Voluntary Association for Rural Reconstruction and Appropriate Technology.

Figure 4

Flow of community feedback in Upscaling Participatory Videos and Action for Agriculture and Nutrition (UPAVAN). PLA, Participatory Learning and Action.