Authors:
Răzvan Rughinis
1
;
Stefania Matei
2
and
Cosima Rughinis
2
Affiliations:
1
University Politehnica of Bucharest, Romania
;
2
University of Bucharest, Romania
Keyword(s):
Smoking Cessation, Android Applications, Quitting Advice, User Profile.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Computer-Supported Education
;
Domain Applications and Case Studies
;
Fuzzy Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Industrial, Financial and Medical Applications
;
Information Technologies Supporting Learning
;
Learning/Teaching Methodologies and Assessment
;
Mentoring and Tutoring
;
Methodologies and Methods
;
Mobile Information Systems
;
Mobile Learning
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
;
Ubiquitous Learning
;
Web Information Systems and Technologies
Abstract:
We analyze in-depth five smoking cessation apps on Android OS, examining how they teach users to quit
smoking and what they learn from users. Apps advise would-be ex-smokers how to perceive the world, how
to deal with their emotions, and how to act on their bodies and environment. Still, they learn little from their
users, and even less from the scientific literature on smoking cessation. We discuss the potential for
improved customization of advice to users’ profiles and we propose a simple inventory of online scientific
resources as a starting point for developers looking to create better apps.