I am your smartphone, and i know you are about to smoke: The application of mobile sensing and computing approaches to smoking research and treatment

F. Joseph McClernon, Romit Roy Choudhury

Research output: Contribution to journalArticlepeer-review

Abstract

Much is known about the immediate and predictive antecedents of smoking lapse, which include situations (e.g., presence of other smokers), activities (e.g., alcohol consumption), and contexts (e.g., outside). This commentary suggests smartphone-based systems could be used to infer these predictive antecedents in real time and provide the smoker with just-in-time intervention. The smartphone of today is equipped with an array of sensors, including GPS, cameras, light sensors, barometers, accelerometers, and so forth, that provide information regarding physical location, human movement, ambient sounds, and visual imagery. We propose that libraries of algorithms to infer these antecedents can be developed and then incorporated into diverse mobile research and personalized treatment applications. While a number of challenges to the development and implementation of such applications are recognized, our field benefits from a database of known antecedents to a problem behavior, and further research and development in this exciting area are warranted.

Original languageEnglish (US)
Pages (from-to)1651-1654
Number of pages4
JournalNicotine and Tobacco Research
Volume15
Issue number10
DOIs
StatePublished - Oct 2013
Externally publishedYes

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

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