Development and evaluation of visualizations of smoking data for integration into the Sense2Quit app for tobacco cessation

Feasibility and Acceptability of the Sense2Quit App for Improving Smoking Cessation in PWH

An estimated 34-47% of PWH in the US report cigarette smoking, three to four times the prevalence observed in the U.S. adult population. Given the dearth of smoking cessation interventions for PWH, our study team used community based participatory feedback to design and develop the Sense2Quit App, an mHealth app linked to a smartwatch, whose sensor technology provides for collection of hand gesture movements to detect when a participant lifts their hand to smoke a cigarette. Participants receive messages through the app to encourage their quit attempts and maintenance of smoking cessation. The goal of this feasibility study was to conduct a randomized feasibility study in 60 PWH living in NYC to assess the feasibility and acceptability of the Sense2Quit App for smoking cessation. Findings from this study suggest that the intervention was highly feasible and acceptable in this population. There was high acceptability with only 1 participant withdrawing from the trial and overall app usage increasing over the course of the study. Participants wore the sensor and used the app and rated it as highly usable. The high retention rate and engagement with the app supports the overall acceptability of this approach. ClinicalTrials.gov Identifier: NCT05609032.

Validating the information technology (IT) implementation framework to Implement mHealth technology for consumers: A case study of the Sense2Quit app for smoking cessation

OBJECTIVE

The goal of this paper was to understand the applicability of the Information Technology (IT) Implementation Framework, a multi-level approach to identify factors that impede or promote IT usage, for incorporating a mHealth technology for consumers in the community setting.

METHODS

A case study of the implementation of the Sense2Quit App for smoking cessation among people living with HIV was examined to parse out the factors within the framework that are applicable to mHealth technology and the factors that may need modification for use of this framework within this context.

RESULTS

Findings suggest that phases two through five of the framework were applicable to our study and phase one was not.

CONCLUSION

Findings support the use of the theory for implementation of mHealth technology for promoting consumer health at the community level. This use case may be useful for stakeholders evaluating implementation of mHealth for patients with chronic conditions as it highlights the need to identify preferences of app specifications, personal habits, and various factors such as confidentiality and digital literacy which may challenge sustained usage.

A Robust Cross-Platform Solution With the Sense2Quit System to Enhance Smoking Gesture Recognition: Model Development and Validation Study

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.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/49558.

Designing visual hierarchies for the communication of health data

OBJECTIVES

Visual hierarchy underlies all visual design decisions related to information presentation. This manuscript describes the experience of a multidisciplinary health data visualization and software design team in using visual hierarchy to redesign a hereditary colorectal cancer lab report.

MATERIALS AND METHODS

A series of interviews with representative users were conducted to identify target user groups and determine information hierarchy for each user type. Visual elements (eg, size, color, contrast, etc.) were then assigned to mirror the information hierarchy and workflow for each user type.

RESULTS

User research identified 2 distinct user groups as consumers of the redesigned lab report. An interactive design employing a 2-level page hierarchy was developed, which stratified the content to support the needs of each user type.

CONCLUSIONS

The challenges related to displaying the complex nature of digital and personal health data can be addressed by applying foundational design methods such as visual hierarchy.

DISCUSSION

Visual hierarchy, a foundational design principle, can be used by visualization teams to clearly and efficiently present complex datasets associated with healthcare.

Pilot Testing of an mHealth App for Tobacco Cessation in People Living With HIV: Protocol for a Pilot Randomized Controlled Trial

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.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05609032; https://clinicaltrials.gov/study/NCT05609032.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/49558.