JMIR Publications

ABSTRACT

Background:

Musculoskeletal (MSK) conditions such as back and joint pain are a growing problem, affecting 18.8 million people in the UK. Digital health interventions (DHIs) are a potentially effective way to deliver information and to support self-management. It is vital that the development of such interventions is transparent, can illustrate how individual components work, how they link back to the theoretical constructs they are attempting to change, and how this might influence outcomes. getUBetter is a DHI developed to address the lack of personalised supported self-management tools available to patients with MSK conditions, by providing knowledge, skills and confidence to navigate through a self-management journey.

Objective:

The aim of this project was to map a logic model of behaviour change for getUBetter, to illustrate how content and functionality of the DHI is aligned with recognised behavioural theory, effective behaviour change techniques (BCTs), and clinical guidelines.

Methods:

A range of behaviour change models and frameworks were used including the behaviour change wheel and persuasive systems design framework to map the logic model of behaviour change underpinning getUBetter. Three main stages included: 1) understanding the behaviour the intervention is attempting to change, 2) identifying which elements of the intervention might bring about the desired change in behaviour, and 3) describing intervention content and how this can be optimally implemented.

Results:

The content mapped to 25 BCTs, including: information about health consequences, instruction on how to perform a behaviour, reducing negative emotions, and verbal persuasion about capability. Mapping to the persuasive system design framework illustrated the use of a number of persuasive design principles, including: tailoring, personalisation, simulation, and reminders.

Conclusions:

This process enabled the proposed mechanisms of action and theoretical foundations of getUBetter to be comprehensively described, highlighting the key techniques utilised to support patients to self-manage their condition. These findings provide guidance for the on-going evaluation of effectiveness (including quality of engagement) of the intervention, and highlight areas which might be strengthened in future iterations.