Evidence map›Paper›PMID 31172967›Full record

Trial reportJournal of medical Internet research2019

Outcomes and Device Usage for Fully Automated Internet Interventions Designed for a Smartphone or Personal Computer: The MobileQuit Smoking Cessation Randomized Controlled Trial.

Brian G Danaher, Milagra S Tyler, Ryann C Crowley, Håvar Brendryen, John R Seeley

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01952236 (Web and Mobile Smoking Cessation Interventions), which is not on this map. Cited by 28 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 5 pooled it
11.2field-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.

NCT01952236 nacompletednot on this map

Web and Mobile Smoking Cessation Interventions

TypeinterventionalSponsorOregon Research InstituteRan2015 to 2018Enrolled1,266ConditionsSmokingArmsWeb+Mobile, Web Only
3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 5 syntheses or guidelines pooled it, 43 citations in OpenAlex.

  1. Guideline
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Digital Help for Substance Users (SU): A Systematic Review.International journal of environmental research and public health · 2022
    Pooled it
  6. Digital Smoking Cessation With a Comprehensive Guideline-Based App-Results of a Nationwide, Multicentric, Parallel, Randomized Controlled Trial in Germany.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2024
    Trial
  7. Trial
  8. Trial
  9. Trial
  10. Trial
  11. Efficacy and Utilization of Smartphone Applications for Smoking Cessation Among American Indians and Alaska Natives: Results From the iCanQuit Trial.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2022
    Trial
  12. Trial
  13. The Put It Out Project (POP) Facebook Intervention for Young Sexual and Gender Minority Smokers: Outcomes of a Pilot, Randomized, Controlled Trial.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2020
    Trial
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Review
  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

5 authors at 2 institutions in 2 countries.

Brian G DanaherPrevention Science Institute, University of Oregon, Eugene, OR, United States.ORCID 0000-0001-8234-0479
Milagra S TylerPrevention Science Institute, University of Oregon, Eugene, OR, United States.ORCID 0000-0003-3207-6248
Ryann C CrowleyOregon Research Institute, Eugene, OR, United States.ORCID 0000-0003-0416-4582
Håvar BrendryenNorwegian Centre for Addiction Research, University of Oslo, Oslo, Norway.ORCID 0000-0003-3860-9754
John R SeeleyPrevention Science Institute, University of Oregon, Eugene, OR, United States.ORCID 0000-0002-5320-7510
Oregon Research Institute · USUniversity of Oslo · NO

Funding

Web and Mobile Smoking Cessation InterventionsR01CA172205 · NCI · OREGON RESEARCH INSTITUTE · PI DANAHER, BRIAN G., SEELEY, JOHN R · 2013 to 2016
$2.6M
NCI NIH HHS R01 CA172205
6 · The paper itself

Abstract

backgroundMany best practice smoking cessation programs use fully automated internet interventions designed for nonmobile personal computers (desktop computers, laptops, and tablets). A relatively small number of smoking cessation interventions have been designed specifically for mobile devices such as smartphones.

objectiveThis study examined the efficacy and usage patterns of two internet-based best practices smoking cessation interventions.

methodsOverall, 1271 smokers who wanted to quit were randomly assigned to (1) MobileQuit (designed for-and constrained its use to-mobile devices, included text messaging, and embodied tunnel information architecture) or (2) QuitOnline (designed for nonmobile desktop or tablet computers, did not include text messages, and used a flexible hybrid matrix-hierarchical information architecture). Primary outcomes included self-reported 7-day point-prevalence smoking abstinence at 3- and 6-month follow-up assessments. Program visits were unobtrusively assessed (frequency, duration, and device used for access).

resultsSignificantly more MobileQuit participants than QuitOnline participants reported quitting smoking. Abstinence rates using intention-to-treat analysis were 20.7% (131/633) vs 11.4% (73/638) at 3 months, 24.6% (156/633) vs 19.3% (123/638) at 6 months, and 15.8% (100/633) vs 8.8% (56/638) for both 3 and 6 months. Using Complete Cases, MobileQuit's advantage was significant at 3 months (45.6% [131/287] vs 28.4% [73/257]) and the combined 3 and 6 months (40.5% [100/247] vs 25.9% [56/216]) but not at 6 months (43.5% [156/359] vs 34.4% [123/329]). Participants in both conditions reported their program was usable and helpful. MobileQuit participants visited their program 5 times more frequently than did QuitOnline participants. Consistent with the MobileQuit's built-in constraint, 89.46% (8820/9859) of its visits were made on an intended mobile device, whereas 47.72% (691/1448) of visits to QuitOnline used an intended nonmobile device. Among MobileQuit participants, 76.0% (459/604) used only an intended mobile device, 23.0% (139/604) used both mobile and nonmobile devices, and 0.1% (6/604) used only a nonmobile device. Among QuitOnline participants, 31.3% (137/438) used only the intended nonmobile devices, 16.7% (73/438) used both mobile and nonmobile devices, and 52.1% (228/438) used only mobile devices (primarily smartphones).

conclusionsThis study provides evidence for optimizing intervention design for smartphones over a usual care internet approach in which interventions are designed primarily for use on nonmobile devices such as desktop computers, laptops. or tablets. We propose that future internet interventions should be designed for use on all of the devices (multiple screens) that users prefer. We forecast that the approach of designing internet interventions for mobile vs nonmobile devices will be replaced by internet interventions that use a single Web app designed to be responsive (adapt to different screen sizes and operating systems), share user data across devices, embody a pervasive information architecture, and complemented by text message notifications.

trial registrationClinicalTrials.gov NCT01952236; https://clinicaltrials.gov/ct2/show/NCT01952236 (Archived by WebCite at http://www.webcitation.org/6zdSxqbf8).

Indexed as

Internet-Based InterventionMicrocomputersSmartphoneSmoking CessationAdultFemaleHealth BehaviorHumansMaleMiddle AgedResearch DesignText MessagingTreatment OutcomedeviceeHealthinternetmHealthsmartphonesmokingtobacco

Identifiers

PMID31172967
PMCPMC6594213
OpenAlexW2991125672

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.