Applications of Digital Health Technologies in the 24-Hour Movement Paradigm
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".
Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 330
Special Issue Editor
Special Issue Information
Dear Colleagues,
Insufficient physical activity, unhealthy sleep, and excessive sedentary time are increasingly common worldwide. These behaviours are also associated with an increased risk of developing a number of chronic diseases, including heart disease, type 2 diabetes, musculoskeletal conditions, and some cancers.
Digital health technologies have the potential to promote healthy behaviours in the population, and represent an accessible and low-cost method for the delivery of interventions aimed at improving lifestyle behaviours. Whilst literature in this area is growing, there are still several gaps that are worthy of further research. There is little data on the use of AI and machine learning in the development of behavioural change interventions to improve 24-hour movement behaviours, and the core components of interventions which will lead to long-term engagement and usage with digital health technologies remain unknown.
This Special Issue aims to publish novel, high-quality contributions related to the development or evaluation of the use of digital health technologies in the promotion of the 24-hour movement paradigm. This Special Issue has a particular focus on evidence synthesis and studies assessing the long-term effectiveness of digital health technologies and novel interventional paradigms utilizing the latest in computational modelling. In addition, this Special Issue is interested in digital health technologies and their use within the personalise medicine framework with regards to the 24-hour movement paradigm.
Dr. James Sanders
Guest Editor
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Keywords
- mHealth
- digital health technology
- physical activity
- sleep
- sedentary behaviour
- machine learning
- AI
- behaviour change
- personalisation
- disease prevention
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