The prevalence of electronic nicotine delivery systems (ENDS) is rising dramatically among both adults and youth and ENDS use is fast becoming a major public health issue. However, because of their recent emergence, researchers know little about ENDS, their use, their effects on human physiology and health, their risks and benefits, or their impact on tobacco control efforts. A common barrier to studying ENDS is the lack of data on objective, real world use of ENDS. Thus, the proposed project aims to adapt existing innovative mobile assessment tools that can be used to target critical ENDS research gaps by providing mobile sensing technology that can objectively collect precise data regarding ENDS use in real time in real world. Specifically, the proposed revision project will expand the scope of Project On Track (1R01CA190329-01A1, PI: Wetter) by extending the application of puffMarker, an existing tool that automatically detects smoking, for the assessment of ENDS use. The current project has three aims: 1) adapt and validate puffMarker to identify discrete episodes of ENDS use, 2) adapt and validate puffMarker to distinguish between cigarette smoking and ENDS use among dual users of ENDS and cigarettes, and 3) utilize the Project On Track protocol to collect real time, real world data investigating potential determinants of ENDS use among both exclusive ENDS users as well as dual users of cigarettes and ENDS. Altogether, 120 participants (30 for Aim 1, 30 for Aim 2, and 60 for Aim 3) will be enrolled. Participants recruited for Aims 1 and 2 will attend laboratory (three 2-hour sessions) and field (3 days) studies. In the laboratory sessions, participants will wear the AutoSense wireless sensors and be asked to use ENDS (Aim 1) or use ENDS and smoke a cigarette (Aim 2). Participants' ENDS and cigarette puffs will be recorded by an independent observer. In the field studies, participants will wear the AutoSense wireless sensors and be asked to use ENDS (Aim 1) or use ENDS and smoke cigarettes (Aim 2). Participants will be asked to record each instance of ENDS use or cigarette smoking on a SP. The goals of the laboratory studies are to collect data to train puffMarker to identify ENDS use and to distinguish between cigarette smoking and ENDS use. The goal of the field studies is to validate puffMarker in real-life, natural environments.
Aim 3 will utilize the Project On Track protocol to collect the first real time, real world data on ENDS and dual use. Participants will be assessed for 6 days using AutoSense, EMA, and GPS to examine potential determinants of ENDS use. A validated puffMarker that detects ENDS use and distinguishes between ENDS use and smoking can enhance many areas of research inquiry on ENDS. Knowledge learned from Aim 3 will be essential for the development of comprehensive conceptual models with respect to ENDS use and smoking cessation.
The proposed project aims to develop an innovative tool that targets important ENDS research gaps by offer- ing researchers the latest mobile sensing technology to objectively collect precise data regarding ENDS use and distinguish between ENDS use and smoking in real time and in real world.
|Vinci, Christine; Haslam, Aaron; Lam, Cho Y et al. (2018) The use of ambulatory assessment in smoking cessation. Addict Behav 83:18-24|
|Bari, Rummana; Adams, Roy J; Rahman, Mahbubur et al. (2018) rConverse: Moment by Moment Conversation Detection Using a Mobile Respiration Sensor. Proc ACM Interact Mob Wearable Ubiquitous Technol 2:|
|Hossain, Syed Monowar; Hnat, Timothy; Saleheen, Nazir et al. (2017) mCerebrum: A Mobile Sensing Software Platform for Development and Validation of Digital Biomarkers and Interventions. Proc Int Conf Embed Netw Sens Syst 2017:|
|Saleheen, Nazir; Chakraborty, Supriyo; Ali, Nasir et al. (2016) mSieve: Differential Behavioral Privacy in Time Series of Mobile Sensor Data. Proc ACM Int Conf Ubiquitous Comput 2016:706-717|
|Adams, Roy J; Saleheen, Nazir; Thomaz, Edison et al. (2016) Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams. Proc Int Conf Mach Learn 48:334-343|
|Chatterjee, Soujanya; Hovsepian, Karen; Sarker, Hillol et al. (2016) mCrave: Continuous Estimation of Craving During Smoking Cessation. Proc ACM Int Conf Ubiquitous Comput 2016:863-874|