Evidence map›Paper›PMID 35831180›Full record

Trial reportJournal of medical Internet research2022

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

Jonathan B Bricker, Kristin E Mull, Margarita Santiago-Torres, Zhen Miao, Olga Perski, Chongzhi Di

Open access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
6.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Trial
  5. Trial
  6. Trial
  7. Trial
  8. Trial
  9. Trial
  10. Trial
  11. Trial
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Jonathan B BrickerDivision of Public Health Sciences, Fred Hutch Cancer Center, Seattle, WA, United States.ORCID 0000-0002-5694-8795
Kristin E MullDivision of Public Health Sciences, Fred Hutch Cancer Center, Seattle, WA, United States.ORCID 0000-0002-7918-3078
Margarita Santiago-TorresDivision of Public Health Sciences, Fred Hutch Cancer Center, Seattle, WA, United States.ORCID 0000-0001-6051-3172
Zhen MiaoDepartment of Statistics, University of Washington, Seattle, WA, United States.ORCID 0000-0001-8575-0879
Olga PerskiDepartment of Behavioural Science and Health, University College London, London, United Kingdom.ORCID 0000-0003-3285-3174
Chongzhi DiDivision of Public Health Sciences, Fred Hutch Cancer Center, Seattle, WA, United States.ORCID 0000-0002-1371-581X
Fred Hutch Cancer Center · USUniversity of Washington · USUniversity College London · GB

Funding

Randomized Trial of an Innovative Smartphone Intervention for Smoking CessationR01CA192849 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BRICKER, JONATHAN B · 2015 to 2019
$3.1M
Cancer Research UK C1417/A22962NCI NIH HHS R01 CA192849
6 · The paper itself

Abstract

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

objectiveIn the context of a randomized trial comparing 2 smartphone apps for smoking cessation, this study aimed to determine distinct groups of smartphone app log-in trajectories over a 6-month period, their association with smoking cessation outcomes at 12 months, and baseline user characteristics that predict data-driven trajectory group membership.

methodsFunctional clustering of 182 consecutive days of smoothed log-in data from both arms of a large (N=2415) randomized trial of 2 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 of smoking abstinence at 12 months. Finally, the baseline characteristics associated with group membership were examined using logistic and multinomial logistic regression. The analyses were conducted separately for each app.

resultsFor iCanQuit, participants were clustered into 3 groups: "1-week users" (610/1069, 57.06%), "4-week users" (303/1069, 28.34%), and "26-week users" (156/1069, 14.59%). For smoking cessation rates at the 12-month follow-up, compared with 1-week users, 4-week users had 50% higher odds of cessation (30% vs 23%; odds ratio [OR] 1.50, 95% CI 1.05-2.14; P=.03), 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 2 groups: "1-week users" (695/1064, 65.32%) and "3-week users" (369/1064, 34.68%). The difference in the odds of being abstinent at 12 months for 3-week users versus 1-week users was minimal (23% vs 21%; OR 1.16, 95% CI 0.84-1.62; P=.37). Different baseline characteristics predicted the trajectory group membership for each app.

conclusionsPatterns of 1-, 3-, and 4-week smartphone app use for smoking cessation may be common in how people engage in digital health interventions. There were significantly higher odds of quitting smoking among 4-week users and especially among 26-week users of the iCanQuit app. 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.

Indexed as

Mobile ApplicationsSmoking CessationHealth BehaviorHumansSmartphoneSmokingacceptance and commitment therapyACTdigital interventionseHealthengagementiCanQuitmHealthmobile healthmobile phoneQuitGuidesmartphone appssmokingtobaccotrajectories

Identifiers

PMID35831180
PMCPMC9437788
OpenAlexW4285102974

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.