PurposePhysical activity promotion has mostly focused on theories of intention-formation, with the assumption that positive intentions will lead to behaviour. Though necessary, exercise intentions alone are often not sufficient to improve physical activity behaviour. The Multi-Process Action Control (M-PAC) framework builds on previous intention-based theories by including both determinants of intention formation and its translation into behaviour. The purpose of this study was to describe the process of developing a self-guided web-based intervention to promote physical activity among adults using the M-PAC model.ProceduresThe development process consisted of the following three phases: 1) Intervention planning: determine intervention needs and requirements; 2) Intervention development: use an iterative process to design a web-based physical activity intervention based on the M-PAC framework; 3) Pilot testing: conduct usability and acceptability assessment on the web-based intervention to further enhance user experience.Principal resultsThe intervention planning phase suggested that there is a need for web-based physical activity interventions and there is currently no web-based intervention designed using the M-PAC model. In phase two, we adopted an iterative process to develop a 10-week self-guided web-based intervention to help adults (>18 years of age) to meet 150 min of moderate to vigorous physical activity per week. The pilot testing phase yielded valuable feedback on usability, content, and design of the web-based intervention.Major conclusionsThe development of a web-based physical activity intervention using the M-PAC model could further enhance the effectiveness of web-based interventions and have a significant impact on extending the reach of existing physical activity promotion programs. This study has reinforced the importance of an iterative development process that involves a multi-disciplinary team to design a web-based intervention to promote physical activity. The process enabled the team to clarify the needs for an intervention for our target users, and provided valuable feedback on the design and content of the web-based intervention. Future studies are now needed to evaluate the effectiveness of our web-based intervention.
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Background A challenge facing researchers conducting mobile health (mHealth) research is the amount of resources required to develop mobile apps. This can be a barrier to generating relevant knowledge in a timely manner. The recent rise of “no-code” software development platforms may overcome this challenge and enable researchers to decrease the cost and time required to develop mHealth research apps. Objective We aimed to describe the development process and the lessons learned to build Pathverse, a no-code mHealth app design platform. Methods The study took place between November 2019 and December 2021. We used a participatory research framework to develop the mHealth app design platform. In phase 1, we worked with researchers to gather key platform feature requirements and conducted an exploratory literature search to determine needs related to this platform. In phase 2, we used an agile software framework (Scrum) to develop the platform. Each development sprint cycle was 4 weeks in length. We created a minimum viable product at the end of 7 sprint cycles. In phase 3, we used a convenience sample of adults (n=5) to gather user feedback through usability and acceptability testing. In phase 4, we further developed the platform based on user feedback, following the V-model software development process. Results Our team consulted end users (ie, researchers) and utilized behavior change technique taxonomy and behavior change models (ie, the multi-process action control framework) to guide the development of features. The first version of the Pathverse platform included features that allowed researchers to (1) design customized multimedia app content (eg, interactive lessons), (2) set content delivery logic (eg, only show new lessons when completing the previous lesson), (3) implement customized participant surveys, (4) provide self-monitoring tools, (5) set personalized goals, and (6) customize app notifications. Usability and acceptability testing revealed that researchers found the platform easy to navigate and that the features were intuitive to use. Potential improvements include the ability to deliver adaptive interventions and add features such as community group chat. Conclusions To our knowledge, Pathverse is the first no-code mHealth app design platform for developing mHealth interventions for behavior. We successfully used behavior change models and the behavior change technique taxonomy to inform the feature requirements of Pathverse. Overall, the use of a participatory framework, combined with the agile and hybrid-agile software development process, enabled our team to successfully develop the Pathverse platform.
BACKGROUND A challenge facing researchers when conducting mobile health (mHealth) research is the resources required to develop mobile apps. This can be a barrier to generating relevant knowledge in a timely manner. The recent rise of “no-code” software development platforms may overcome this challenge and enable researchers to decrease the cost and time required to develop mHealth research apps. OBJECTIVE To describe the development process and the lessons learned to build the no-code mHealth app design platform (Pathverse). METHODS The study took place between November 2019 to December 2021. In phase 1, we used a participatory research frame to gather key platform feature requirements. In phase 2, we used an agile software framework to develop the platform. In phase 3, we gathered user feedback through usability and acceptability testing. In phase 4, we further developed the platforms based on user feedback. RESULTS Our team consulted end-users (i.e. researchers) and utilized behaviour change technique (BCT) taxonomy and behaviour change models (i.e. multi-process action control framework) to guide the features developed. The first version of the Pathverse platform included features that allowed researchers to 1) design customized multimedia app content (e.g., interactive lessons), 2) set content delivery logic (e.g. only show new lessons when completing the previous lesson), 3) implement customized participant surveys, 4) provide self-monitoring tools 5) set personalized goals 6) customize app notification. Usability and acceptability testing revealed that researchers found the platform easy to navigate, and the features were initiative to use. Potential improvements included the ability to deliver adaptive interventions and add features such as community group chat. CONCLUSIONS To our knowledge, Pathverse is the first no-code mHealth app design platform for developing behaviour mHealth interventions. We successfully used behaviour change models and the BCT taxonomy to inform the feature requirements of Pathverse. Overall, the use of a participatory framework, combined with the agile and hybrid-agile software development process, enabled our team to successfully develop the Pathverse platform.
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