Health, Smoking
Conditions
Keywords
smoking, healthy, smartphone
Brief 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.
Detailed 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.
Interventions
BEHAVIORAL48 hour smoking abstinence
Participants will maintain smoking abstinence for 48 hours
OTHERSmartphone
Participants will use an Android-based smartphone as their own for one month
Sponsors
Duke University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
BASIC_SCIENCE
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
Yes
Inclusion criteria
* generally healthy * between the ages of 18 and 65 * smoking of at least 10 cig/day of a brand delivering ≥ 0.5 mg nicotine (FTC method) for \> 1 year AND an afternoon expired CO concentration \>5 ppm (to confirm inhalation) or morning urinary cotinine \> 100 ng/mL * willingness to carry and use a study smartphone as their own for one month
Exclusion criteria
* inability to attend all required sessions * use of smokeless tobacco products * current use of nicotine replacement therapy or other smoking cessation treatment
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in smoking behaviors as measured by an algorithm of social variables | up to 4 weeks | phone calls (time, duration, coded identity of contact, including smoking status); SMS texting (time sent, coded identity of contact) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Change in smoking behaviors as measured by an algorithm of device interaction variables | up to 4 weeks | running applications; applications installed; screen status |
| Change in smoking behaviors as measured by an algorithm of motion variables | up to 4 weeks | acceleration; direction and magnitude of gravity; device orientation |
| Change in smoking behaviors as measured by an algorithm of environmental variables | up to 4 weeks | light; proximity; magnetic field; pressure; temperature |
| Change in smoking behaviors as measured by an algorithm of positioning variables | up to 4 weeks | location; Bluetooth devices within range; available WiFi access points; ID for the current cell tower the device is connected to |
Countries
United States
Outcome results
None listed