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Developing Mobile Health Interventions With Implementation in Mind: Application of the Multiphase Optimization Strategy (MOST) Preparation Phase to Diabetes Prevention Programming

With thousands of mobile health (mHealth) solutions on the market, patients and health care providers struggle to identify which solution to use and prescribe. The lack of evidence-based mHealth solutions may be because of limited research on intervention development and the continued use of traditi...

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Detalles Bibliográficos
Autores principales: MacPherson, Megan, Merry, Kohle, Locke, Sean, Jung, Mary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092234/
https://www.ncbi.nlm.nih.gov/pubmed/35471473
http://dx.doi.org/10.2196/36143
Descripción
Sumario:With thousands of mobile health (mHealth) solutions on the market, patients and health care providers struggle to identify which solution to use and prescribe. The lack of evidence-based mHealth solutions may be because of limited research on intervention development and the continued use of traditional research methods for mHealth evaluation. The Multiphase Optimization Strategy (MOST) is a framework that aids in developing interventions that produce the best-expected outcomes (ie, effectiveness), given constraints imposed on affordability, scalability, and efficiency (also known as achieving intervention EASE). The preparation phase of the MOST highlights the importance of formative intervention development—a stage often overlooked and rarely published. The aim of the preparation phase of the MOST is to identify candidate intervention components, create a conceptual model, and define the optimization objective. Although the MOST sets these 3 targets, no guidance is provided on how to conduct quality research within the preparation phase and what specific steps can be taken to identify potential intervention components, develop the conceptual model, and achieve intervention EASE with the implementation context in mind. To advance the applicability of the MOST within the field of implementation science, this study provides an account of the methods used to develop an mHealth intervention using the MOST. Specifically, we provide an example of how to achieve the goals of the preparation phase by outlining the formative development of an mHealth-prompting intervention within a diabetes prevention program. In addition, recommendations are proposed for future researchers to consider when conducting formative research on mHealth interventions with implementation in mind. Given its considerable reach, mHealth has the potential to positively affect public health by decreasing implementation costs and improving accessibility. The MOST is well-suited for the efficient development and optimization of mHealth interventions. By using an implementation-focused lens and outlining the steps in developing an mHealth intervention using the preparation phase of the MOST, this study may guide future intervention developers toward maximizing the impact of mHealth outside academia.