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// Detecting Smoking 'Opportunity' Context Using Mobile Sensors

SmokingOpp

Context plays a key role in impulsive adverse behaviors such as fights, suicide attempts, binge-drinking, and smoking lapse. Several contexts dissuade such behaviors, but some may trigger adverse impulsive behaviors. We define these latter contexts as ‘opportunity’ contexts, as their passive detection from sensors can be used to deliver context-sensitive interventions.

In SmokingOpp, we define the general concept of ‘opportunity’ contexts and apply it to the case of smoking cessation. We operationalize the smoking ‘opportunity’ context, using self-reported smoking allowance and cigarette availability. We show its clinical utility by establishing its association with smoking occurrences using Granger causality. Next, we mine several informative features from GPS traces, including the novel location context of smoking spots, to develop the SmokingOpp model for automatically detecting the smoking ‘opportunity’ context. Finally, we train and evaluate the SmokingOpp model using 15 million GPS points and 3,432 self-reports from 90 newly abstinent smokers in a smoking cessation study.

Details & Specifications
Published:
Category:
Frameworks, Models, Technologies
Tags:
GPS
Mobile computing
Smoking Cessation
Ubiquitous computing

SmokingOpp Statistics

million
GPS points

The study collected over 15 million GPS points across 1,519 person-days.

Participants

SmokingOpp collected information from 126 participants, though for modeling purposes, participants with no location data for more than 3 consecutive days were excluded, leaving 90 participants.