mHealth: opportunities and challenges for diabetes intervention research
Background: Traditionally, health intervention evaluations provide long-term evidence of efficacy and safety via validated protocols, following a positivist paradigm, or approach, to research. However, modern mobile health (mHealth) technologies develop too quickly and outside of medical regulation, making it challenging for health research to keep pace.
Objective: This thesis explored and tested how research can incorporate mHealth approaches and resources to evaluate mHealth interventions comprehensively, which follows the pragmatism paradigm. The works described herein were part of a larger project that designed, developed, and tested a data-sharing system between patients and their healthcare providers (HCPs) during diabetes consultations.
Methods: The pragmatism paradigm underpins the mixed-methods, multi-phase design approach to exploring this overall objective. The following methods were performed using a sequential exploratory strategy. First, co-design workshops invited individuals with diabetes and HCPs to design an mHealth data-sharing system. Next, a scoping literature review identified research practices for evaluating mHealth interventions to-date. Then, app usage-logs, collected from a previous longitudinal study, were analyzed to explore how much additional information they could provide about patients’ self-management. Finally, a mixed-method study was designed to test the feasibility of combining both traditional and mHealth approaches and resources to evaluate an intervention.
Results: Using the pragmatist paradigm as a scaffolding, these works provide evidence of how research can provide more comprehensive knowledge about mHealth interventions for diabetes care and self-management. Nine individuals with diabetes and six HCPs participated in the co-design workshops. Feedback included how a data-sharing system should work between patients and providers. The literature review identified how both traditional and mHealth-based approaches (n=15 methods, n=21 measures) were used together to evaluate mHealth interventions. Usage-log analysis revealed that changes in Glycosylated haemoglobin (HbA1c) differed between groups organized by usage patterns and duration of use of mHealth. The mixed-method study demonstrated how to collect comprehensive and complementary information when combining traditional and mHealth-centered approaches and resources.
Conclusion: Traditional positivist approaches and resources are not adequate, on their own, to comprehensively understand the impact of mHealth interventions. The presented studies demonstrate that it is both feasible and prudent to combine traditional research with mHealth approaches, such as analyzing usage-logs, arranging co-design workshops, and other patient-centered methods in a pragmatist approach to produce comprehensive evidence of mHealth’s impacts on both patients and HCPs.
Paper 1: Bradway, M., Morris, R.L., Giordanengo, A. & Årsand, E. (2020). How mHealth can facilitate collaboration in diabetes care: qualitative analysis of co-design workshops. BMC Health Services Research, 20, 1104. Also available in Munin at https://hdl.handle.net/10037/20191.
Paper 2: Bradway, M., Gabarron, E., Johansen, M., Zanaboni, P., Jardim, P., Joakimsen, R., Pape-Haugaard, L. & Årsand, E. (2020). Methods and Measures Used to Evaluate Patient-Operated Mobile Health Interventions: Scoping Literature Review. JMIR mhealth and uhealth, 8(4), e16814. Also available in Munin at https://hdl.handle.net/10037/18576.
Paper 3: Bradway, M., Pfuhl, G., Joakimsen, R., Ribu, L., Grøttland, A. & Årsand, E. (2018). Analysing mHealth usage logs in RCTs: Explaining participants’ interactions with type 2 diabetes self-management tools. PLoS ONE, 13(8), e0203202. Also available in Munin at https://hdl.handle.net/10037/14033.
Paper 4: Bradway, M., Giordanengo, A., Joakimsen, R., Hansen, A.H., Grøttland, A., Hartvigsen, G., Randine, P. & Årsand, E. (2020). Measuring the Effects of Sharing Mobile Health Data During Diabetes Consultations: Protocol for a Mixed Method Study. JMIR Research Protocols, 9(2), e16657. Also available in Munin at https://hdl.handle.net/10037/17915.
PublisherUiT The Arctic University of Norway
UiT Norges arktiske universitet
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