Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Feb 14, 2019
Date Accepted: May 27, 2019
Predictors of retention in an adult text-messaging smoking cessation intervention program
ABSTRACT
Background:
Mobile health tools, such as text-messaging programs, can effectively support smoking cessation. However, high rates of disengagement from these tools decreases their effectiveness.
Objective:
The purpose of this study was to identify user characteristics associated with retention in an adult text-messaging smoking cessation intervention.
Methods:
Data were collected to assess level of nicotine addiction, frequency of being around other smokers, time of day for cigarette cravings, extrinsic and intrinsic motivation to quit smoking, confidence in quitting, and long-term intention to be smoke free among adults initiating a quit attempt using the publicly available program, SmokefreeTXT between March 6 and June 21, 2016 (n=6215 users). Multivariable survival analysis modeling time to opt out was conducted to identify characteristics associated with opting out over the course of the intervention adjusting for age, sex, smoking frequency, if a user reset their quit date, and number of days enrolled before initiating the quit attempt. Among those who opted out, multivariable logistic regression analysis was used to identify predictors of opting out early (within 2 days into the quit attempt) compared to opting out late (more than 2 days into the quit attempt), adjusting for the same confounders.
Results:
Survival analyses indicated that younger age, female sex, higher levels of nicotine addiction, lower intention to be smoke free, and enrolling in SmokefreeTXT one week or less before initiating the quit attempt were associated with an increased risk of opting out. Specifically, users who smoked within five minutes of waking were 1.17 times more likely to opt out compared to those who smoked more than 5 minutes after waking (95% CI: 1.01,1.35). Users with anything other than high long-term intention to be smoke free were 1.29 times more likely to opt out compared to those with the highest levels of intention (95% CI: 1.04,1.59). Among users who opted out from SmokefreeTXT, logistic regression modeling indicated that compared to users who were never or rarely around other smokers, those who were sometimes around other smokers had 2.25 the odds of opting out early (95% CI: 1.33, 3.81). Also, compared to users with low levels of extrinsic motivation to quit smoking, users with the highest levels of extrinsic motivation had 1.58 the odds of opting out early (95% CI: 1.03, 2.42). Users who reset their quit date after initiating a quit attempt were less likely to opt out, compared with those who did not reset their quit date.
Conclusions:
Several user characteristics are associated with retention in an adult smoking cessation text-messaging program. These results provide guidance on potential characteristics to address in future smoking cessation text-messaging programs. Providing additional support to users with these characteristics may increase retention in text-messaging programs, and ultimately smoking cessation.
Citation
