Background: An estimated 40% of people living with HIV smoke cigarettes. Although smoking rates in the United States have been declining in recent years, people living with HIV continue to smoke cigarettes at twice the rate of the general population. Mobile health (mHealth) technology is an effective tool for people living with a chronic illness, such as HIV, as currently 84% of households in the United States report that they have a smartphone. Although many studies have used mHealth interventions for smoking cessation, few studies have recruited people living with HIV who smoke. Objective: The objective of the pilot randomized controlled trial (RCT) is to examine the feasibility, acceptability, and preliminary efficacy of the Sense2Quit App as a tool for people living with HIV who are motivated to quit smoking. Methods: The Sense2Quit study is a 2-arm RCT for people living with HIV who smoke cigarettes (n=60). Participants are randomized to either the active intervention condition, which consists of an 8-week supply of nicotine replacement therapy, standard smoking cessation counseling, and access to the Sense2Quit mobile app and smartwatch, or the control condition, which consists of standard smoking cessation counseling and a referral to the New York State Smokers’ Quitline. The Sense2Quit app is a mobile app connected through Bluetooth to a smartwatch that tracks smoking gestures and distinguishes them from other everyday hand movements. In the Sense2Quit app, participants can view their smoking trends, which are recorded through their use of the smartwatch, including how often or how much they smoke and the amount of money that they are spending on cigarettes, watch videos with quitting tips, information, and distractions, play games, set reminders, and communicate with a study team member. Results: Enrollment of study participants began in March 2023 and is expected to end in October 2023. All data collection is expected to be completed by the end of January 2024. This RCT will test the difference in outcomes between the control and intervention arms. The primary outcome will be the percentage of participants with biochemically verified 7-day point prevalence smoking or tobacco abstinence at their 12-week follow-up. Results from this pilot study will be disseminated to the research community following the completion of all data collection. Conclusions: The Sense2Quit study leverages mHealth so that it can help smokers improve their efforts at smoking cessation. Our research has the potential to not only increase quitting rates among people living with HIV who may need a prolonged, tailored intervention but also inform further development of mHealth for people living with HIV. This mHealth study will contribute significant findings to the greater mHealth research community, providing evidence as to how mHealth should be developed and tested among the target population.
Background: Smoking is a leading cause of preventable death, and people with HIV have higher smoking rates and are more likely to experience smoking-related health issues. The Sense2Quit study introduces innovative advancements in smoking cessation technology by developing a comprehensive mobile app that integrates with smartwatches to provide real-time interventions for people with HIV attempting to quit smoking. Objective: We aim to develop an accurate smoking cessation app that uses everyday smartwatches and an artificial intelligence model to enhance the recognition of smoking gestures by effectively addressing confounding hand gestures that mimic smoking, thereby reducing false positives. The app ensures seamless usability across Android (Open Handset Alliance [led by Google]) and iOS platforms, with optimized communication and synchronization between devices for real-time monitoring. Methods: This study introduces the confounding resilient smoking model, specifically trained to distinguish smoking gestures from similar hand-to-mouth activities used by the Sense2Quit system. By incorporating confounding gestures into the model’s training process, the system achieves high accuracy while maintaining efficiency on mobile devices. To validate the model, 30 participants, all people with HIV who smoked cigarettes, were recruited. Participants wore smartwatches on their wrists and performed various hand-to-mouth activities, including smoking and other gestures such as eating and drinking. Each participant spent 15 to 30 minutes completing the tasks, with each gesture lasting 5 seconds. The app was developed using the Flutter framework to ensure seamless functionality across Android and iOS platforms, with robust synchronization between the smartwatch and smartphone for real-time monitoring. Results: The confounding resilient smoking model achieved an impressive F1-score of 97.52% in detecting smoking gestures, outperforming state-of-the-art models by distinguishing smoking from 15 other daily hand-to-mouth activities, including eating, drinking, and yawning. Its robustness and adaptability were further confirmed through leave-one-subject-out evaluation, demonstrating consistent reliability and generalizability across diverse individuals. The cross-platform app, developed using Flutter (Google), demonstrated consistent performance across Android and iOS devices, with only a 0.02-point difference in user experience ratings between the platforms (iOS 4.52 and Android 4.5). The app’s continuous synchronization ensures accurate, real-time tracking of smoking behaviors, enhancing the system’s overall utility for smoking cessation. Conclusions: Sense2Quit represents a significant advancement in smoking cessation technology. It delivers timely, just-in-time interventions through innovations in cross-platform communication optimization and the effective recognition of confounding hand gestures. These improvements enhance the accuracy and accessibility of real-time smoking detection, making Sense2Quit a valuable tool for supporting long-term cessation efforts among people with HIV trying to quit smoking.