Application of the behaviour change wheel framework to the development of interventions within the City4Age project

Abstract

The probability of an intervention being effective is likely increased if it is designed following a behavioural analysis and with the aid of evidence-based intervention frameworks. For example, the Behaviour Change Wheel (BCW) framework and its associated COM-B model of behaviour have been used successfully as a starting point for designing behaviour change interventions. However, the BCW framework can also be applied at a later stage in the design process, such as when an intervention has been designed but before it is deployed. Here we describe the application of the BCW framework and COM-B model to evaluate and refine already designed interventions. We use a multidisciplinary multi-site project (‘City4Age’) as a case study. The project aims to promote independent living of older adults through the deployment of interventions using wearable and environment-based technology. We conducted face-to-face interviews with site representatives to identify the target behaviours, perceived barriers and facilitators, intervention functions, and modes of delivery for each planned intervention. Additionally, literature reviews were conducted to identify evidence-based facilitators and barriers for each targeted behaviour. Subsequently, we 1) compared the intervention functions proposed by the project-sites with those most likely to be effective according to the BCW; and 2) assessed the congruency of the barriers and facilitators identified by the pilot-sites with those identified in the literature. For five planned interventions across two project-sites (Birmingham and Singapore), two had intervention functions unlikely to be effective according to the BCW. The two planned interventions to promote social engagement did not address barriers or facilitators evident in the literature, indicating they required refinement. Applying the BCW framework allowed to identify which interventions needed refining. It also helped in providing specific guidance in our recommendations for improvements prior to deployment.