JMIR mHealth and uHealth
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JMIR mHealth and uHealth · Dec 2019
Randomized Controlled TrialDevelopment and Local Contextualization of Mobile Health Messages for Enhancing Disease Management Among Community-Dwelling Stroke Patients in Rural China: Multimethod Study.
Rural China has experienced an increasing health burden because of stroke. Stroke patients in rural communities have relatively poor awareness of and adherence to evidence-based secondary prevention and self-management of stroke. Mobile technology represents an innovative way to influence patient behaviors and improve their self-management. ⋯ By applying multiple methodologies and conducting a pilot study, we designed and fine-tuned a voice message-based intervention package for promoting secondary prevention among community-dwelling stroke patients in rural China. Design of the content and dispatching algorithm should engage both experts and end users and adequately consider the needs and preferences of recipients.
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JMIR mHealth and uHealth · Dec 2019
Review Historical ArticleDigital Health Behavior Change Technology: Bibliometric and Scoping Review of Two Decades of Research.
Research on digital technology to change health behavior has increased enormously in recent decades. Due to the interdisciplinary nature of this topic, knowledge and technologies from different research areas are required. Up to now, it is not clear how the knowledge from those fields is combined in actual applications. A comprehensive analysis that systematically maps and explores the use of knowledge within this emerging interdisciplinary field is required. ⋯ Closer cooperation and interaction between behavioral sciences and technological areas is needed, so that theoretical knowledge and new technological advancements are better connected in actual applications. Eventually, this could result in a larger societal impact, an increase of the effectiveness of digital technologies for health behavioral change, and more insight in the relationship between behavioral change strategies and persuasive technologies' effectiveness.
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JMIR mHealth and uHealth · Dec 2019
Use of Mobile Health Apps and Wearable Technology to Assess Changes and Predict Pain During Treatment of Acute Pain in Sickle Cell Disease: Feasibility Study.
Sickle cell disease (SCD) is an inherited red blood cell disorder affecting millions worldwide, and it results in many potential medical complications throughout the life course. The hallmark of SCD is pain. Many patients experience daily chronic pain as well as intermittent, unpredictable acute vaso-occlusive painful episodes called pain crises. These pain crises often require acute medical care through the day hospital or emergency department. Following presentation, a number of these patients are subsequently admitted with continued efforts of treatment focused on palliative pain control and hydration for management. Mitigating pain crises is challenging for both the patients and their providers, given the perceived unpredictability and subjective nature of pain. ⋯ The Microsoft Band 2 allowed easy collection of objective, physiologic markers during an acute pain crisis in adults with SCD. Features can be extracted from these data signals and matched with pain scores. Machine learning models can then use these features to feasibly predict patient pain scores.