Jul 13, 2017 · In the end, this work is in service of providing the most effective mobile intervention[s]. The interventions might be in the form of various ...
Introduction to part IV: Predictors to mHealth interventions. Authors. Susan A. Murphy, University of Michigan, Ann Arbor · James M. Rehg, Georgia Institute of ...
The interventions might be in the form of various services that are available 24/7. In the lingo of mobile health, these interventions could be delivered in the ...
Jul 24, 2017 · Bibliographic details on Introduction to Part IV: Predictors to mHealth Interventions.
Introduction to part IV: Predictors to mHealth interventions. Murphy, S. A., Rehg, J. M. & Kumar, S., Jul 12 2017, Mobile Health: Sensors, Analytic Methods ...
Nov 26, 2023 · This study presents an evidence-based model that provides an insight to policymakers, health organizations, governments, and political leaders ...
In this review, we aimed to describe measures of patient engagement with mHealth interventions and the effects of engagement on HF outcomes.
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Introduction to Part III: Markers to mHealth Predictors. 345-348. view ... Introduction to Part IV: Predictors to mHealth Interventions. 437-441. view.
Mobile Health: Sensors, Analytic Methods, and Applications
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The book offers an in-depth exploration of the three key elements of mHealth technology: the development of on-body sensors that can identify key health-related ...
Introduction to Part IV: Predictors to mHealth Interventions. Abstract. The previous three parts provided examples of mobile health applications, a description ...