Evidence map›Paper›PMID 37606969›Full record

Observational studyJournal of medical Internet research2023

Use of the Smoking Cessation App Ex-Smokers iCoach and Associations With Smoking-Related Outcomes Over Time in a Large Sample of European Smokers: Retrospective Observational Study.

Marthe Bl Mansour, Wim B Busschers, Mathilde R Crone, Kristel M van Asselt, Henk C van Weert, Niels H Chavannes, Eline Meijer

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 2 institutions in 1 country.

Marthe Bl MansourDepartment of General Practice, Academic Medical Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, Netherlands.ORCID 0000-0003-4991-9520
Wim B BusschersDepartment of General Practice, Academic Medical Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, Netherlands.ORCID 0000-0002-3393-9511
Mathilde R CroneDepartment of Public Health & Primary Care, Leiden University Medical Centre, Leiden, Netherlands.ORCID 0000-0003-1243-858X
Kristel M van AsseltDepartment of General Practice, Academic Medical Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, Netherlands.ORCID 0000-0001-9679-2177
Henk C van WeertDepartment of General Practice, Academic Medical Centre Amsterdam, Amsterdam University Medical Centres, Amsterdam, Netherlands.ORCID 0000-0001-6370-4724
Niels H ChavannesDepartment of Public Health & Primary Care, Leiden University Medical Centre, Leiden, Netherlands.ORCID 0000-0002-8607-9199
Eline MeijerDepartment of Public Health & Primary Care, Leiden University Medical Centre, Leiden, Netherlands.ORCID 0000-0001-7078-5067
University of Amsterdam · NLLeiden University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital interventions are increasingly used to support smoking cessation. Ex-smokers iCoach was a widely available app for smoking cessation used by 404,551 European smokers between June 15, 2011, and June 21, 2013. This provides a unique opportunity to investigate the uptake of a freely available digital smoking cessation intervention and its effects on smoking-related outcomes.

objectiveWe aimed to investigate whether there were distinct trajectories of iCoach use, examine which baseline characteristics were associated with user groups (based on the intensity of use), and assess if and how these groups were associated with smoking-related outcomes.

methodsAnalyses were performed using data from iCoach users registered between June 15, 2011, and June 21, 2013. Smoking-related data were collected at baseline and every 3 months thereafter, with a maximum of 8 follow-ups. First, group-based modeling was applied to detect distinct trajectories of app use. This was performed in a subset of steady users who had completed at least 1 follow-up measurement. Second, ordinal logistic regression was used to assess the baseline characteristics that were associated with user group membership. Finally, generalized estimating equations were used to examine the association between the user groups and smoking status, quitting stage, and self-efficacy over time.

resultsOf the 311,567 iCoach users, a subset of 26,785 (8.6%) steady iCoach users were identified and categorized into 4 distinct user groups: low (n=17,422, 65.04%), mild (n=4088, 15.26%), moderate (n=4415, 16.48%), and intensive (n=860, 3.21%) users. Older users and users who found it important to quit smoking had higher odds of more intensive app use, whereas men, employed users, heavy smokers, and users with higher self-efficacy scores had lower odds of more intensive app use. User groups were significantly associated with subsequent smoking status, quitting stage, and self-efficacy over time. For all groups, over time, the probability of being a smoker decreased, whereas the probability of being in an improved quitting stage increased, as did the self-efficacy to quit smoking. For all outcomes, the greatest change was observed between baseline and the first follow-up at 3 months. In the intensive user group, the greatest change was seen between baseline and the 9-month follow-up, with the observed change declining gradually in moderate, mild, and low users.

conclusionsIn the subset of steady iCoach users, more intensive app use was associated with higher smoking cessation rates, increased quitting stage, and higher self-efficacy to quit smoking over time. These users seemed to benefit most from the app in the first 3 months of use. Women and older users were more likely to use the app more intensively. Additionally, users who found quitting difficult used the iCoach app more intensively and grew more confident in their ability to quit over time.

Indexed as

Mobile ApplicationsSmoking CessationEx-SmokersFemaleHumansMaleSmokersSmokingdigital smoking cessation interventionengagementEuropean smokersmobile phonesmoker characteristicssmoking cessation appsmoking-related outcomestrajectories of use patternsuser groups

Identifiers

PMID37606969
PMCPMC10481207
OpenAlexW4386047084

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.