L
Laura H. Barg-Walkow
Researcher at Georgia Institute of Technology
Publications - 20
Citations - 407
Laura H. Barg-Walkow is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Health care & Usability. The author has an hindex of 8, co-authored 18 publications receiving 314 citations. Previous affiliations of Laura H. Barg-Walkow include Boston Children's Hospital.
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A longitudinal study of emoticon use in text messaging from smartphones
TL;DR: To understand how emoticons are used in text messaging and, in particular, how genders differed in the frequency and variety of emoticons used via this medium, data is collected from individuals' smartphones over a 6-month period.
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Self-Management of Wellness and Illness in an Aging Population
TL;DR: This chapter reviews the last 10 years of literature on self-management of illnesses and wellness in the context of an aging population, wherein middle-aged adults are more likely to be managing wellness activities and older adults are often managing both maintenance of health and chronic illnesses.
Journal ArticleDOI
Mobile Health Apps: Improving Usability for Older Adult Users:
Stephanie A. Morey,Rachel E. Stuck,Amy W. Chong,Laura H. Barg-Walkow,Tracy L. Mitzner,Wendy A. Rogers +5 more
TL;DR: This work evaluated the usability of one medication management app and two congestive heart failure management apps using cognitive walkthroughs, heuristic analysis, and user testing, and identified design issues that may affect usability for older users, including poor navigation, small button sizes, and inadequate data visualizations.
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Managing Heart Failure On the Go: Usability Issues with mHealth Apps for Older Adults:
TL;DR: An assessment of human factors issues for common mHealth apps designed for managing congestive heart failure and encouraging mHealth app designers to improve usability by providing easier navigation, streamlining data entry processes, and providing clear recovery from errors.
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The effect of incorrect reliability information on expectations, perceptions, and use of automation
TL;DR: Introductory statements describing artificially low automation reliability have a long-lasting impact on perceptions about automation performance, which generally stayed the same or increased with experience using the system.