Ali, Abdallah El and Heuten, Wilko and Matviienko, Andrii and Boll, Susanne and Feld, Yannick (2016) VapeTracker: Tracking vapor consumption to help E-cigarette users quit. In: CHI 2016 : #chi4good ; proceedings ; The 34rd Annual CHI Conference on Human Factors in Computing Systems, San Jose, CA, USA, May 07 - 12, 2016. ACM, Association for Computing Machinery, New York, NY, pp. 2049-2056. ISBN 978-1-4503-3362-7

Full text not available from this repository. (Request a copy)

Abstract

Despite current controversy over e-cigarettes as a smoking cessation aid, we present early work based on a web survey (N=249) that shows that some e-cigarette users (46.2%) want to quit altogether, and that behavioral feedback that can be tracked can fulfill that purpose. Based on our survey findings, we designed VapeTracker, an early prototype that can attach to any e-cigarette device to track vaping activity. We discuss our future research on vaping cessation, addressing how to improve our VapeTracker prototype, ambient feedback mechanisms, and the future inclusion of behavior change models to support quitting e-cigarettes.

Item Type:	Book Section
Uncontrolled Keywords:	behavior change technology, e-cigarettes, habits, health, OFFIS, prototype, sensors, tracking, UNI, vapetracker, vaping
Divisions:	School of Computing Science, Business Administration, Economics and Law > Department of Computing Science
Date Deposited:	06 Apr 2017 10:48
Last Modified:	06 Apr 2017 10:48
URI:	https://oops.uni-oldenburg.de/id/eprint/3110
URN:	urn:nbn:de:gbv:715-oops-31918
DOI:
Nutzungslizenz:

Actions (login required)

View Item