Text to quit: Challenges and opportunities in automated tobacco treatment outreach

Despite improvements over time, tobacco smoking remains the leading cause of preventable death in the United States, with 15% of adults reporting ongoing tobacco use. Effective treatments for tobacco dependence remain underutilized, particularly among historically marginalized populations such as those of lower income and from racial and ethnic minority groups. As a result, those who could benefit most from cessation efforts are often least likely to receive them. Responsibility for addressing smoking cessation typically falls to clinicians, who face competing priorities during time-limited office visits and may lack sufficient resources or education to provide effective counseling. Pragmatic approaches that engage patients directly in tobacco treatment, particularly those that use readily available electronic health record (EHR) data, offer ongoing opportunities to increase access to tobacco treatment, reduce disparities, and improve patient outcomes.

In this issue of CHEST, Cartujano-Barrera et al describe a pragmatic randomized clinical trial that evaluated methods of directly offering patients tobacco treatment. At 2 sites, 2,826 Latino adults with active tobacco use, as documented in the EHR, received text messages that offered them enrollment in a tobacco treatment intervention. Each participant received 1 of 6 conditions with the use of a factorial design that varied whether the patient received (a) no monetary incentive when enrolling in the treatment program, a small fixed monetary amount for enrolling, or a chance of winning a larger monetary amount for enrolling; and (b) either 1 or 4 cycles of text messages. The authors then assessed rates of enrollment in the smoking cessation text messaging intervention according to these random assignments, which resulted in patient enrollment up to 5.4%. Although monetary incentives did not increase enrollment in the cessation text messaging intervention, sending patients more text messages resulted in a significantly higher likelihood of enrollment. However, patients who received more messages were also more likely to opt out of all messages; nearly 30% of the patients declined further text messages. This phenomenon has been seen in other text message-based research, in which individuals who receive more messages are more likely to opt out of the program and future messages altogether. Further, enrollment rates were low regardless of strategy; rates ranged from 1.3% to 5.4%, and the authors do not present results on whether the tobacco treatment intervention was effective at achieving tobacco abstinence among those who enrolled.

Remy Bremner, Joanna L Hart