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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: May 2, 2022
Date Accepted: Jul 13, 2022
Date Submitted to PubMed: Jul 13, 2022

The final, peer-reviewed published version of this preprint can be found here:

Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial

Bricker J, Mull K, Santiago-Torres M, Miao Z, Perski O, Di C

Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial

J Med Internet Res 2022;24(8):e39208

DOI: 10.2196/39208

PMID: 35831180

PMCID: 9437788

Smoking cessation smartphone application use over time: Do usage patterns predict 12-month cessation outcomes?

  • Jonathan Bricker; 
  • Kristin Mull; 
  • Margarita Santiago-Torres; 
  • Zhen Miao; 
  • Olga Perski; 
  • Chongzhi Di

ABSTRACT

Background:

Background:

Little is known about how individuals engage over time with smartphone application interventions and whether this engagement predicts health outcomes.

Objective:

Objectives: In the context of a randomized trial comparing two smartphone applications (apps) for smoking cessation, to determine: (1) distinct groups of smartphone app login trajectories over a 6-month period, (2) their association with smoking cessation outcomes at 12-months, and (3) baseline user characteristics that predict data-driven trajectory group membership.

Methods:

Methods:

Functional clustering of 182 consecutive days of smoothed login data from both arms of a large (N = 2415) randomized trial of two smartphone apps for smoking cessation (iCanQuit and QuitGuide) was used to identify distinct trajectory groups. Logistic regression was used to determine the association of group membership with the primary outcome of 30-day point prevalence smoking abstinence at 12 months. Finally, baseline characteristics associated with group membership were examined using logistic and multinomial logistic regression. Analyses were conducted separately for each app.

Results:

Results:

For iCanQuit, participants were clustered into three groups: “1-week users” (n=610, 57% of the sample), “4-week users” (n=303, 28%), and “26-week users” (n=156, 15%). For smoking cessation rates at the 12-month follow-up, compared to 1-week users, 4-week users had 50% higher odds of cessation (30% vs. 23%; OR = 1.50; 95% CI = 1.05, 2.14; p = .027) whereas 26-week users had 397% higher odds (56% vs. 23%; OR = 4.97; 95% CI = 3.31, 7.52; p < .001). For QuitGuide, participants were clustered into two groups: “1-week users” (n=695, 65% of the sample), and “3-week users” (n=369, 35%). The difference in the odds of being abstinent at 12-months for 3-week users vs. 1-week users was minimal (23% vs. 21%; OR = 1.16; 95% CI = 0.84, 1.62; p = .370). Different baseline characteristics predicted trajectory group membership for each app.

Conclusions:

Conclusions:

Patterns of 1-, 3-, and 4-week usage of smartphone apps for smoking cessation may be common for how people engage in digital health interventions. There were significant higher odds of quitting smoking among 4-week users, and especially among 26-week users of the iCanQuit application. To improve study outcomes, strategies for detecting users who disengage early from these interventions (1-week users) and proactively offering them a more intensive intervention could be fruitful. Clinical Trial: Clinical Trials.gov Registration Number: NCT02724462


 Citation

Please cite as:

Bricker J, Mull K, Santiago-Torres M, Miao Z, Perski O, Di C

Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial

J Med Internet Res 2022;24(8):e39208

DOI: 10.2196/39208

PMID: 35831180

PMCID: 9437788

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