Summary A common issue among digital health applications is that they are based on project‐specific solutions and are developed from scratch, which results in redundant development and lack of data and technology reuse. This can be seen in, for example, building study specific websites and mobile frontends, deploying customized infrastructures, and collecting data that may have been collected in other studies and projects. However, existing data and technology are not easily shareable between projects due to large investment required to address data exchanging mechanism, data and technology sovereignty, data security and resource discovery, while the benefit for the resource owners is uncertain. In this article, we present a supporting framework, named DHLink, to address this issue on two fronts. First, the DHLink framework securely connects multiple digital health applications, facilitates real‐time data sharing, and supports rapid application development by reusing data and technology. Second, to aid in rapid development of new digital health applications, a set of highly generic and reusable microservices has been developed as the initial resources available in the DHLink ecosystem. Two proof‐of‐concept use cases outlined show the effectiveness of DHLink for both data sharing between existing applications, and rapid development of a new application.
Aim: To determine whether a digital nudge soon after dinner reduces after-dinner snacking events as measured objectively by continuous glucose monitoring (CGM) in patients with type 2 diabetes (T2D).Methods: This is a single-site micro-randomized trial (MRT). People with T2D, aged 18-75 years, managed with diet or a stable dose of oral antidiabetic medications for at least 3 months, and who habitual snack after dinner at least 3 nights per week, will be recruited. Picto-graphic nudges were designed by mixed research methods. After a 2-week lead-in phase to determine eligibility and snacking behaviours by a CGM detection algorithm developed by the investigators, participants will be microrandomized daily (1:1) to a second 2-week period to either a picto-graphic nudge delivered-in-time (Intui Research) or no nudge. During lead-in and MRT phases, 24-hour glucose will be measured by CGM, sleep will be tracked by an undermattress sleep sensor, and dinner timing will be captured daily by photographing the evening meal.Results: The primary outcome is the difference in the incremental area under the CGM curve between nudging and non-nudging days during the period from 90 minutes after dinner until 04:00 AM. Secondary outcomes include the effect of baseline characteristics on treatment, and comparisons of glucose peaks and time-inrange between nudging and non-nudging days. The feasibility of 'just-in-time' messaging and nudge acceptability will be evaluated, along with the analysis of sleep quality measures and their night-to-night variability.Conclusions: This study will provide preliminary evidence of the impact of appropriately timed digital nudges on 24 -hour intertitial glucose levels resulting from altered after-dinner snacking in people with T2D. An exploratory sleep substudy will provide evidence of a bidirectional relationship between after-dinner snacking behaviour, glycaemia and sleep. Ultimately, this study will allow for the design of a future confirmatory study of the potential for digital nudging to improve health related behaviours and health outcomes.
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