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      From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques

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          The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

          The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
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            Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support

            Background The just-in-time adaptive intervention (JITAI) is an intervention design aiming to provide the right type/amount of support, at the right time, by adapting to an individual’s changing internal and contextual state. The availability of increasingly powerful mobile and sensing technologies underpins the use of JITAIs to support health behavior, as in such a setting an individual’s state can change rapidly, unexpectedly, and in his/her natural environment. Purpose Despite the increasing use and appeal of JITAIs, a major gap exists between the growing technological capabilities for delivering JITAIs and research on the development and evaluation of these interventions. Many JITAIs have been developed with minimal use of empirical evidence, theory, or accepted treatment guidelines. Here, we take an essential first step towards bridging this gap. Methods Building on health behavior theories and the extant literature on JITAIs, we clarify the scientific motivation for JITAIs, define their fundamental components, and highlight design principles related to these components. Examples of JITAIs from various domains of health behavior research are used for illustration. Conclusions As we enter a new era of technological capacity for delivering JITAIs, it is critical that researchers develop sophisticated and nuanced health behavior theories capable of guiding the construction of such interventions. Particular attention has to be given to better understanding the implications of providing timely and ecologically sound support for intervention adherence and retention We clarify the scientific motivation for the Just-In-Time Adaptive Interventions, define its fundamental components, and discuss key design principles for each component.
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              A survey of mobile phone sensing

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                Author and article information

                Contributors
                Journal
                IEEE Internet of Things Journal
                IEEE Internet Things J.
                Institute of Electrical and Electronics Engineers (IEEE)
                2327-4662
                2372-2541
                September 1 2022
                September 1 2022
                : 9
                : 17
                : 15413-15434
                Affiliations
                [1 ]Big Data Lab, Baidu Inc., Beijing, China
                [2 ]Big Data Lab, Baidu Research, Baidu Inc., Beijing, China
                [3 ]Department of Computer Science, Peking University, Beijing, China
                [4 ]School of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, China
                [5 ]Department of Engineering Systems and Environment, University of Virginia, Charlottesville, VA, USA
                [6 ]Institut Polytechnique de Paris, Telecom SudParis, Evry Cedex, France
                Article
                10.1109/JIOT.2022.3161046
                ae8ec1ec-b945-4eff-9b87-b1ac85f55abf
                © 2022

                https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-037

                History

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