The development of 'Make One Small Change': an e-health intervention for the workplace developed using the Person-Based Approach

Background The application of digital health interventions is widespread and many employers are implementing employee e-health programs. Intended to enhance productivity by increasing wellbeing, workplace interventions often lack evidence of effectiveness and have low rates of retention. Use of the person-based approach (PBA) is one solution, which offers a systematic framework for developing effective digital health interventions. This paper describes the application of the PBA to the development of 'Make one small change' (Cigna MSC (TM)), an online behaviour change system for lifestyle habits focused on resilience, movement, eating and sleep. Method and results The development of Cigna MSC (TM) took place over four stages with colleagues (n = 79) across Cigna globally. Application of the PBA entailed using high amounts of qualitative data to inform development and a cyclical process of 'listening, applying and delivering' was adhered to throughout. Early stages involved review of current literature and the collection of feedback in relation to existing interventions. Combined, results revealed key intervention development issues that were then used to form guiding principles. Guiding principles ensured intervention objectives translated into relevant design features. The final stages of evaluation included testing images, text and content approaches. Feedback dictated that the intervention should be fun, easy to use and include milestones for self-monitoring. The resulting version was finalised and made ready to pilot so future analysis can be made in relation to real-world engagement and the embedded evaluative content can be used to provide evidence of intervention effectiveness. Conclusions Using the PBA, which was evolved specifically to improve development of digital interventions, resulted in a workplace intervention embedded with in-depth user input combined with evidenced-based theory. This paper illustrates how using a rigorous methodology can drive the creation of an effective digital health intervention that uniquely allows for refinement at each stage.