To realise an improvement in practice, a Learning Health System often requires patients, clinicians and others to change their behaviour. There are many theories and models that can be deployed to understand and aid this process. The Behaviour Change Wheel (BCW) (Figure I) [159] is a systematic approach to designing, implementing and evaluating behaviour change interventions in any setting. It is based on a collection of existing theoretical frameworks.
The BCW represents a theory of what drives behaviour and how it can be influenced in different situations. This leads to an accessible and rigorous process that can be integrated into a Learning Health System, increasing the likelihood that the knowledge generated will result in behaviour associated with better outcomes.
The hub of the BCW is concerned with understanding the behaviour that has to be changed. This is achieved using the COM-B model (Figure J).
Changing the behaviour of an individual, group or population requires a change in capability, opportunity and motivation, or some combination of the three. Standardised questionnaires have already been developed [159] to capture the drivers of a particular behaviour.
The next circle in the wheel outlines the possible intervention functions. These are broad categories of means by which an intervention can change behaviour: Education, Persuasion, Incentivisation, Coercion, Training, Enablement, Modelling, Environmental Restructuring and Restrictions [159].
The BCW guide provides a matrix that links the COM-B model to the intervention functions [159]. For example, if the barrier to behaviour change is identified as Physical Capability, then Training and Enablement are potential functions that the intervention could serve. If the barrier to change has been identified as relating to Reflective Motivation, then the intervention could serve the functions of Education, Persuasion, Incentivisation and Coercion (or a combination of these).
The final element on the BCW is the set of possible policy categories: seven ways that policy could deliver the intervention. These include Communication/Marketing, Guidelines, Fiscal Measures, Regulation, Legislation, Environmental/Social Planning and Service Provision [159]. Again, a matrix has been created in the BCW guide that links intervention functions to policy categories.
In order to operationalise the BCW, the intervention functions are linked to Behaviour Change Techniques (BCTs), which are the smallest active components of an intervention and designed to change behaviour (eg self-monitoring, goal setting, action planning etc). A taxonomy of 93 techniques has been developed that can be used to describe BCTs used in interventions. The most frequently used BCTs have been mapped onto the intervention functions of the BCW.
The BCW enables a theoretical and systematic approach to intervention design. The COM-B model can be used to analyse user data and help “diagnose” what needs to shift in order for change to occur. Guided by matrices in the BCW guide, the most appropriate intervention functions, policy categories and BCTs for the context, behaviour and population of the intervention can be selected [159].
Elements of this process could be automated within a Learning Health System. Crucially, evidence could be collected on the effectiveness and cost-effectiveness of each of the BCTs in various situations, resulting in further learning. There are examples of the BCW being integrated in the design of mHealth apps [160]. Behaviour change will be necessary for patients, clinicians and organisations to adopt elements of the Learning Health System, and to ensure that they act on the evidence generated.
The BCW has been constructed from an analysis of existing frameworks and has been assessed in terms of its reliability in practice [159]. If it is to improve healthcare outcomes, any Learning Health System must have a method for delivering behaviour change [7]. It is also important to note that these approaches operate best in a well-understood system and may fail to produce reproducible results in a complex system.