Dropout and Abstinence Outcomes in a National Text Messaging Smoking Cessation Intervention for Pregnant Women, SmokefreeMOM: Observational Study

Abstract

BackgroundPopulation-level text messaging smoking cessation interventions may reduce racial and ethnic differences in smoking among pregnant women.ObjectiveOur objective was to examine racial and ethnic differences in dropout, response, and abstinence rates among users of a US national, publicly available text messaging cessation intervention targeting pregnant women, SmokefreeMOM.MethodsParticipants were online subscribers to SmokefreeMOM who set a prospective quit date within the 9 months before their due date. We examined demographics, smoking frequency, number of cigarettes smoked per day, and prequit time (up to 14 days of preparation time before quit date) as correlates of response rate and abstinence at 8 time points: quit date, day 7, day 14, day 21, day 28, day 35, day 42 (intervention end), and day 72 (1-month follow-up). We conducted survival analysis of time from quit date to dropout by race and ethnicity.ResultsThe mean age of the analytic sample of 1288 users was 29.46 (SD 7.11) years. Of these, 65.81% (848/1288) were white, 16.04% (207/1288) were black, 8.86% (114/1288) were Latina, and 9.29% (120/1288) were multiracial, American Indian/Alaska Native, Native Hawaiian Pacific Islander, or other; 82.68% (1065/1288) had some college education or less. Point-prevalence abstinence was 14.51% (157/1082) on quit day, 3.51% (38/1082) at intervention end, and 1.99% (21/1053) at 1-month follow-up. Black users (hazard ratio 0.68, 95% CI 0.51-0.91) and those with a high school degree or less (hazard ratio 0.66, 95% CI 0.49-0.89) or some college education (hazard ratio 0.75, 95% CI 0.57-0.99) were less likely to drop out than whites or users with a bachelor’s degree or higher. Response and abstinence rates were similar across race, ethnicity, and education.ConclusionsEnrollment was low among racial and ethnic minority women but high among less-educated women. Abstinence at intervention end and 1-month follow-up was lower than that in controlled trials of text messaging cessation interventions for pregnant women (range 7%-20%). Increasing the reach, engagement, and effectiveness of SmokefreeMOM, especially among women with high rates of smoking during pregnancy, must be prioritized.

Effect of digital health, biomarker feedback and nurse or midwife-led counselling interventions to assist pregnant smokers quit: a systematic review and meta-analysis

“…Pregnant adolescent only studies, studies that did not quantify effect of intervention on pregnant smokers, post hoc analysis of original studies, feasibility, acceptability and development of interventions only,27 36–47 study protocols48–56 and studies with no comparator,24 57–65 no full text66 67 or non-English were excluded. A full list of inclusion and exclusion criteria can be found in online supplemental file 1.…”

Leveraging Digital Technology to Support Pregnant and Early Parenting Women in Recovery from Addictive Substances: A Scoping Review

“…Results from a program evaluation where traditional in-person care services changed to telehealth delivery were reported in two articles [25,26]. A mixed methods design [37] and mixed-methods analysis approach [29] were used by other investigators, and seven studies were described as using pilot, observational, or feasibility designs [28,[38][39][40][41][42][43].…”

“…The two most common digital interventions in the identified studies used were mobile phones and computer platforms. Mobile phones were used to deploy text-messaging strategies to decrease substance use or promote drug abstinence [25,27,[31][32][33][43][44][45]. Mobile phones were also used for telephone counseling [46,47], as well as an e-learning smoking cessation program accessible via smartphone with Internet access [35].…”

“…All ten studies targeting nicotine use or smoking involved pregnant women as participants [27,28,35,38,[43][44][45][46][47]53]. Of the six RCTs, text messaging was the most common digital intervention (n = 3) [27,44,45].…”

Implementation: The Next Giant Hurdle to Clinical Transformation With Digital Health (Preprint)

“…JMIR has been publishing manuscripts related to focused implementation of digital health technologies for two decades. From papers focused on lessons learned [8] to mixed methods studies looking for a deeper understanding of digital health in practice [9], studies of which delivery modality works best [10], and understanding characteristics of digital health among nonusers/nonadopters and users/adopters and reasons for continued engagement or dropout to gain a deeper understanding [11][12][13][14][15][16][17], JMIR journals have been a welcoming home for this work.…”