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Clinical Trial Summary

Smokers will use a smartphone app on a smartphone provided for the study that will passively sense and record information about their activities. Information collected from the smartphone app will be used to develop future smartphone apps that will predict when an individual is at risk of smoking.


Clinical Trial Description

Smokers will carry an Android-based smartphone, which they are to use as their own for one month. After using the smartphone for two weeks, they will abstain from smoking for 48 hours. The phone will passively sense and record information from onboard sensors and send that information to a central server. When server based algorithms detect a pattern of signals likely associated with smoking behavior, the smoker will be queried regarding their current state (smoking?, not smoking but likely to in the next 10 minutes?, etc.). Likewise, when smokers are about to smoke but were not queried, they can indicate they are about to smoke. This information will be used to update algorithms using machine learning techniques. As such, in this study investigators will gain knowledge that will increase understanding of antecedents of smoking behavior and improve the accuracy with which smoking risk can be detected. ;


Study Design

Intervention Model: Single Group Assignment, Masking: Open Label, Primary Purpose: Basic Science


Related Conditions & MeSH terms


NCT number NCT02116283
Study type Interventional
Source Duke University
Contact
Status Completed
Phase N/A
Start date March 2014
Completion date May 2014

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