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Clinical Studies

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  • Wearable Augmented Prediction of Burnout in Nurses: A Synergy of Engineering, Bioethics, Nursing and Wellness Sciences Rochester, Minn., Jacksonville, Fla.

    This research project’s vision is to develop a technology to predict burnout in RNs by combining workplace, psychological, and physiological factors, and exploring the barriers to adopting such a technology.

    Aim 1 is to create a unique, open-access, de-identified dataset that transforms the science of burnout internationally and informs the interaction of continuous physiological measures (measured from smart watches) and repeated psychological and work-related factors for predicting burnout in RNs at Mayo Clinic’s Florida and Rochester sites.

    Aim 2 is to develop an analytical framework combining probabilistic graphical models (PGMs) and multitask learning (MTL) to derive interpretable predictions of burnout using the data gathered in Aim 1. 

    Finally, two supplemental analytical aims of this project are to examine burnout impact on absenteeism and related costs for RNs, and to assess the impact of burnout on nursing-sensitive outcomes.

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