UMB Digital Archive > School of Nursing > Summer Institute in Nursing Informatics (SINI) >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10713/8020

Title: What factors predict Fitbit adherence in Stroke and Parkinson disease?
Schrader_FitbitPrediction_2017.pdf  (142.81 kB)  
Authors: Schrader, Katrina
Mentis, Helena Marie
Phipps, Michael, M.D.
Gruber-Baldini, Ann L.
Yarbrough, Karen L.
Barr, Erik
von Coelln, Rainer
Shulman, Lisa M.
Date: 2017-07-13
Subject Keywords: health information technology
Fitbit
activity monitoring
University of Maryland, Baltimore. School of Nursing
Nursing informatics
Medical Informatics
Comorbidity
Description: Abstract of a poster presentation delivered at the University of Maryland School of Nursing, Summer Institute in Nursing Informatics (SINI) 2017: Clinical Practice, Health and the Internet of Things.
Type: Abstract
Conference/Congress
Poster/Presentation
Appears in Collections:Summer Institute in Nursing Informatics (SINI)

This item is licensed under a Creative Commons License
Creative Commons

Items in UMB Digital Archive are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Contact Us | Terms and Conditions of Use | Privacy | Disclaimer

Copyright © 2011-2012 Health Sciences & Human Services Library. All Rights Reserved.