Combining Persuasive System Design Principles and Behavior Change Techniques in Digital Interventions Supporting Long-term Weight Loss Maintenance: Design and Development of eCHANGE

Background: Long-term weight maintenance after weight loss is challenging, and innovative solutions are required. Digital technologies can support behavior change and, therefore, have the potential to be an effective tool for weight loss maintenance. However, to create meaningful and effective digital behavior change interventions that support end user values and needs, a combination of persuasive system design (PSD) principles and behavior change techniques (BCTs) might be needed. Objective: This study aimed to investigate how an evidence-informed digital behavior change intervention can be designed and developed by combining PSD principles and BCTs into design features to support end user values and needs for long-term weight loss maintenance. Methods: This study presents a concept for how PSD principles and BCTs can be translated into design features by combining design thinking and Agile methods to develop and deliver an evidence-informed digital behavior change intervention aimed at supporting weight maintenance. Overall, 45 stakeholders participated in the systematic and iterative development process comprising co-design workshops, prototyping, Agile development, and usability testing. This included prospective end users (n=17, 38%; ie, people with obesity who had lost ≥8% of their weight), health care providers (n=9, 20%), healthy volunteers (n=4, 9%), a service designer (n=1, 2%), and stakeholders from the multidisciplinary research and development team (n=14, 31%; ie, software developers; digital designers; and eHealth, behavior change, and obesity experts). Stakeholder input on how to operationalize the design features and optimize the technology was examined through formative evaluation and qualitative analyses using rapid and in-depth analysis approaches. Results: A total of 17 design features combining PSD principles and BCTs were identified as important to support end user values and needs based on stakeholder input during the design and development of eCHANGE, a digital intervention to support long-term weight loss maintenance. The design features were combined into 4 main intervention components: Week Plan, My Overview, Knowledge and Skills, and Virtual Coach and Smart Feedback System. To support a healthy lifestyle and continued behavior change to maintain weight, PSD principles such as tailoring, personalization, self-monitoring, reminders, rewards, rehearsal, praise, and suggestions were combined and implemented into the design features together with BCTs from the clusters of goals and planning, feedback and monitoring, social support, repetition and substitution, shaping knowledge, natural consequences, associations, antecedents, identity, and self-belief. Conclusions: Combining and implementing PSD principles and BCTs in digital interventions aimed at supporting sustainable behavior change may contribute to the design of engaging and motivating interventions in line with end user values and needs. As such, the design and development of the eCHANGE intervention can provide valuable input for future design and tailoring of evidence-informed digital interventions, even beyond digital interventions in support of health behavior change and long-term weight loss maintenance

Factors Influencing the Use of a Web-Based Application for Supporting the Self-Care of Patients with Type 2 Diabetes: A Longitudinal Study

Background:\ud The take-up of eHealth applications in general is still rather low and user attrition is often high. Only limited information is available about the use of eHealth technologies among specific patient groups.\ud \ud Objective:\ud The aim of this study was to explore the factors that influence the initial and long-term use of a Web-based application (DiabetesCoach) for supporting the self-care of patients with type 2 diabetes.\ud \ud Methods:\ud A mixed-methods research design was used for a process analysis of the actual usage of the Web application over a 2-year period and to identify user profiles. Research instruments included log files, interviews, usability tests, and a survey.\ud \ud Results:\ud The DiabetesCoach was predominantly used for interactive features like online monitoring, personal data, and patient–nurse email contact. It was the continuous, personal feedback that particularly appealed to the patients; they felt more closely monitored by their nurse and encouraged to play a more active role in self-managing their disease. Despite the positive outcomes, usage of the Web application was hindered by low enrollment and nonusage attrition. The main barrier to enrollment had to do with a lack of access to the Internet (146/226, 65%). Although 68% (34/50) of the enrollees were continuous users, of whom 32% (16/50) could be defined as hardcore users (highly active), the remaining 32% (16/50) did not continue using the Web application for the full duration of the study period. Barriers to long-term use were primarily due to poor user-friendliness of the Web application (the absence of “push” factors or reminders) and selection of the “wrong” users; the well-regulated patients were not the ones who could benefit the most from system use because of a ceiling effect. Patients with a greater need for care seemed to be more engaged in long-term use; highly active users were significantly more often medication users than low/inactive users (P = .005) and had a longer diabetes duration (P = .03).\ud \ud Conclusion:\ud Innovations in health care will diffuse more rapidly when technology is employed that is simple to use and has applicable components for interactivity. This would foresee the patients’ need for continuous and personalized feedback, in particular for patients with a greater need for care. From this study several factors appear to influence increased use of eHealth technologies: (1) avoiding selective enrollment, (2) making use of participatory design methods, and (3) developing push factors for persistence. Further research should focus on the causal relationship between using the system’s features and actual usage, as such a view would provide important evidence on how specific technology features can engage and captivate users

Why Business Modeling is Crucial in the Development of eHealth Technologies

The impact and uptake of information and communication technologies that support health care are rather low. Current frameworks for eHealth development suffer from a lack of fitting infrastructures, inability to find funding, complications with scalability, and uncertainties regarding effectiveness and sustainability. These issues can be addressed by defining a better implementation strategy early in the development of eHealth technologies. A business model, and thus business modeling, help to determine such an implementation strategy by involving all important stakeholders in a value-driven dialogue on what the technology should accomplish. This idea also seems promising to eHealth, as it can contribute to the whole development of eHealth technology. We therefore suggest that business modeling can be used as an effective approach to supporting holistic development of eHealth technologies. The contribution of business modeling is elaborated in this paper through a literature review that covers the latest business model research, concepts from the latest eHealth and persuasive technology research, evaluation and insights from our prior eHealth research, as well as the review conducted in the first paper of this series. Business modeling focuses on generating a collaborative effort of value cocreation in which all stakeholders reflect on the value needs of the others. The resulting business model acts as the basis for implementation. The development of eHealth technology should focus more on the context by emphasizing what this technology should contribute in practice to the needs of all involved stakeholders. Incorporating the idea of business modeling helps to cocreate and formulate a set of critical success factors that will influence the sustainability and effectiveness of eHealth technology