Blaga Oana M, Dascal Marina D, Onișor Alexandra, Frățilă Teodora, Morar Andreea, Mihu Dan, Iuhas Cristian I, Caracostea Gabriela, Mureșan Daniel, Foley Kristie, Resnicow Ken, Meghea Cristian I
Department of Obstetrics, Gynecology and Reproductive Biology, Michigan State University, East Lansing, Michigan, USA
Universitatea Babes-Bolyai, Cluj-Napoca, Romania.
BMJ Open. 2025 Mar 24;15(3):e100259. doi: 10.1136/bmjopen-2025-100259.
Smoking in pregnancy negatively impacts the mother's and offspring's health. Mobile health, especially mobile phone-based approaches, shows promise in supporting pregnant women to quit smoking. Our previous research indicated that support from laypersons, such as family, friends and coworkers, can increase smoking cessation. Building on these findings, we developed an innovative smartphone application (app) that combines the power of social support with artificial intelligence. The app leverages the unique functionality of smartphones and reinforcement learning (RL) to provide a deeply tailored intervention that continuously adapts while emphasising positive support through reciprocal interactions between the smoker and the support person. Herein, we report the methods used to develop, implement and test the feasibility and effectiveness of a novel adaptive mobile pregnancy tobacco cessation app-based intervention using deep tailoring and a self-nominated supporter.
The study is a type II hybrid effectiveness-implementation randomised controlled trial. In total, 300 pregnant smokers and their supporters will be randomised to (1) the SmokeFree Together 2.0 app and an RL-based intervention that continuously decides if a counselling call is needed using a fixed algorithm measuring motivation and craving or (2) a control group. The intervention will be administered throughout pregnancy up to 1 month after giving birth, with a 5-month follow-up period and outcome assessments at 3-month and 6-month post partum. Cessation (primary outcome) is defined as 7-day point biochemically verified prevalence of tobacco use and abstinence since birth, assessed at 6 months post partum. The central hypothesis is that the intervention will show evidence of feasibility and effectiveness in increasing social support, pregnancy cessation and postnatal abstinence.
The Institutional Review Board of Michigan State University (#IRB00000297) approved this trial. The findings will be disseminated through peer-reviewed publications and participation in scientific conferences.
NCT05337722.
1.3 from 15.05.2024.
孕期吸烟会对母亲和后代的健康产生负面影响。移动健康，尤其是基于手机的方法，在支持孕妇戒烟方面显示出前景。我们之前的研究表明，家人、朋友和同事等非专业人士的支持可以增加戒烟成功率。基于这些发现，我们开发了一款创新的智能手机应用程序（应用），它将社会支持的力量与人工智能相结合。该应用利用智能手机的独特功能和强化学习（RL）来提供深度定制的干预措施，这种干预措施会不断调整，同时通过吸烟者与支持人员之间的相互互动强调积极支持。在此，我们报告用于开发、实施和测试一种基于新型自适应移动孕期戒烟应用的干预措施的可行性和有效性的方法，该干预措施采用深度定制和自我提名的支持者。
该研究是一项II型混合有效性 - 实施随机对照试验。总共300名孕期吸烟者及其支持者将被随机分为两组：（1）使用“一起无烟2.0”应用以及基于RL的干预措施，该干预措施使用一种测量动机和渴望程度的固定算法持续决定是否需要进行咨询电话干预；（2）对照组。干预措施将在整个孕期直至产后1个月实施，随访期为5个月，并在产后3个月和6个月进行结果评估。戒烟（主要结局）定义为产后6个月时经生化验证的自出生以来7天内烟草使用和戒烟的患病率。核心假设是该干预措施将在增加社会支持、孕期戒烟和产后戒烟方面显示出可行性和有效性的证据。
密歇根州立大学机构审查委员会（#IRB00000297）批准了该试验。研究结果将通过同行评审出版物和参加科学会议进行传播。
NCT05337722。
2024年5月15日的1.3版。
