This evidence emerged as the Obama administration made higher ed policy a greater focus in the second term, with a particular emphasis on expanding college opportunity for underrepresented students. Recent experimental studies show that these statewide and national text campaigns have not had the same impact on college enrollment or persistence as we estimated in the initial RCTs.
Fast forward to the present, however, and numerous recent experimental studies show that these statewide and national text campaigns have not had the same impact on college enrollment or persistence as we estimated in the initial RCTs. Nor does the efficacy of large-scale text campaigns seem to vary based on content framing, timing, delivery method, or the offer of one-on-one assistance. To paraphrase Nobel Prize—winning economist Richard Thaler, nudges should make it easier for people to follow through on their own intentions or to pursue opportunities and resources that they see as beneficial.
Text campaigns at scale might remind people of what they have to do, but for the reasons I outline below, they might not make completing important and complex tasks such as applying for financial aid much easier for the student or family. Implementing text nudges at scale involves design trade-offs that may reduce campaign efficacy. Implementing a texting campaign with hundreds of thousands of students may require organizations to forego advising and have texts provide just one-way content or to have large caseloads that limit how much engagement advisors can have with individual students.
Another trade-off is that students may have less trust in a state agency or national nonprofit sending the messages. Earlier texting campaigns may have been effective in part because the outreach came from a school or nonprofit and in some cases a specific counselor with whom students had a direct relationship. Highly customized content may have made the messages more salient to students, and correspondingly students may have been less responsive to what they perceived to be more generic information.
Even local text campaigns may face obstacles to efficacy that similar campaigns did not encounter to the same degree a decade ago. Signal Vine, the texting platform with whom we collaborated on our first summer melt projects, now lists dozens of institutional partners on its website.
Omit if volume number precedes. Doctor of Philosophy. Avoid using with an exclamation mark. II of 3 vols. Adj Improper use of adjective. Awk Awkward expression or construction. Ref Unclear pronoun reference. SS Faulty sentence structure. Smith Ph. MLA Washington, D. Congress Cong. Congressional Record d. English ed. French front. Participants who did not complete the survey online were contacted over telephone by research staff blind to treatment assignment.
Text messages and emails were used as a final means of gathering abstinence data from nonresponders. Scores of 3 or more defined a positive screen.
Participants were instructed to consider use of all nicotine-containing vaping devices including JUUL, mods, and other e-cigarettes when answering these questions.
Primary outcome analyses compared day point prevalence abstinence ppa at 7 months postrandomization in study arms using the glm function in R software, version 4.
As described in the study protocol, 20 we first conducted an ITT analysis in which participants lost to follow-up were assumed to be treatment failures ie, vaping. We assessed the success of the IPRW approach in reducing selection bias due to nonresponse by comparing standardized mean differences SMD in baseline characteristics between respondents and nonrespondents.
To identify potential moderators of the treatment-outcome relationship, we examined interactions between treatment assignment and variables presented in Table 1 details of these analyses are outlined in eAppendix 1 in Supplement 2. We also conducted stratified outcome analyses by level of nicotine dependence vape within 30 minutes after waking vs not to assess whether treatment effects persisted among those with higher dependence levels.
At 1 month, the response rate was At 7 months, the response rate was The mean SD age of the participants was Of the total sample, Participants reported a strong desire to quit vaping mean [SD], 4. Past day use of other substances was as follows: cigarettes, No between-arm differences exceeded an SMD of 0. As shown in Table 2 , day ppa rates at 7 months under ITT were A multivariate logistic regression model with 7-month response status as the outcome identified Hispanic ethnicity, sexual minority status, current student status, and PHQ-2 score as predictors of study retention, with current student status and PHQ-2 score resulting in nondifferential attrition by study arm.
Table 2 also shows 7-day ppa under IPRW and ITT analyses; TIQ yielded higher quit rates than control under both analytic approaches, though effect sizes were smaller than those for day ppa. Sensitivity analyses based on multiple imputation modeling confirmed the robustness of ITT estimates eAppendix 2 and eTable 2 in Supplement 2.
Analyses of all variables in Table 1 as potential moderators of treatment effects on day ppa rates under both ITT and IPRW analysis yielded no statistically significant findings eTable 3 in Supplement 2. In stratified analyses focused on time to first vape, ITT abstinence rates among those who reported vaping within 30 minutes of waking were slightly lower in both study arms but still favored TIQ over control Among those who reported vaping 30 minutes after waking, ITT abstinence rates were higher in both study arms with no difference between TIQ and control As shown in Table 3 , TIQ participants reported higher levels of intervention satisfaction compared with control participants across all items.
Results of this randomized clinical trial demonstrated the effectiveness of a tailored, interactive text message intervention for vaping cessation among YAs compared with an assessment-only control. Participants randomized to TIQ were one-third more likely to quit vaping at the 7-month primary end point compared with control participants. Estimates of the treatment benefit appear robust to assumptions about missing data, as response rates were similar in both arms.
Furthermore, the superiority of the intervention was consistent across all demographic variables and vaping characteristics examined, including nicotine dependence, social influences to vape, and other substance use.
The high absolute magnitude of quit rates in both arms is encouraging and worthy of further exploration. Although, to our knowledge, there are no studies of vaping cessation interventions available for comparison, smoking cessation interventions among young people have generally performed less well.
Finally, the trial was conducted during the unprecedented social disruption of the COVID pandemic, which may have affected quit rates in a variety of ways. Strengths of this study include a large and diverse sample across a number of demographic characteristics race, sexual orientation, income that was representative of the population from which it was drawn.
Two potential limitations are worth noting. We did not conduct biochemical verification of abstinence given the demonstrated challenges in digital cessation studies, 41 , 42 the lack of demand characteristics that would give rise to misreporting, 43 , 44 and the selection of day abstinence as a more rigorous primary end point. Second, this study did not include teens, in whom rates of e-cigarette use are highest.
Future research should evaluate its effectiveness in this age group. This randomized clinical trial demonstrated the effectiveness of a tailored, interactive text message intervention in promoting vaping cessation among YAs. Text messaging is a scalable and cost-efficient approach to delivering vaping cessation treatment on a population basis. These results establish a benchmark of effectiveness for other vaping cessation programs and begin to fill an important gap in understanding how to help young people quit e-cigarettes.
Published Online: May 17, Corresponding Author: Amanda L. Author Contributions: Drs Graham and Papandonatos had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Critical revision of the manuscript for important intellectual content: Graham, Amato, Jacobs, Bottcher, Papandonatos. Dr Papandonatos reports receiving personal fees from Truth Initiative as a statistical consultant as well as grants from the National Institutes of Health.
Data Sharing Statement: See Supplement 3. Additional Contributions: We are grateful for the contributions of the entire study team, including Nora Apt and Jenna Woodward, MPH, who were paid interns at Truth Initiative during the conduct of the study and who assisted with data collection.
We also appreciate the study participants who helped to advance the science of vaping cessation for young people. Our website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy Continue. Download PDF Comment. Visual Abstract. View Large Download. Table 1. Learn English abroad with us Find out more. We'd love to stay in touch Get the latest on travel, languages and culture with our newsletter.
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