Evidence map›Paper›PMID 29880466›Full record

ArticleJMIR serious games2018

A Mobile Game to Support Smoking Cessation: Prototype Assessment.

Bethany R Raiff, Nicholas Fortugno, Daniel R Scherlis, Darion Rapoza

Abstract read
In one paragraph

Article in JMIR serious games, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
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

16 citing papers in PubMed.

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  6. Pilot trial of QuitBet: A digital social game that pays you to stop smoking.Experimental and clinical psychopharmacology · 2022
    Article
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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

4 authors.

Bethany R Raiff *Health and Behavioral Integrated Treatments Research Unit, Department of Psychology, Rowan University, Glassboro, NJ, United States.ORCID http://orcid.org/0000-0002-1434-6550
Nicholas FortugnoPlaymatics, LLC, New York, NY, United States.ORCID http://orcid.org/0000-0003-1490-7554
Daniel R ScherlisEntertainment Science, Inc, Durham, NC, United States.ORCID http://orcid.org/0000-0001-7891-5882
Darion Rapoza *Entertainment Science, Inc, Durham, NC, United States.ORCID http://orcid.org/0000-0002-3537-6951

Funding

Treatment Development & Evaluation CoreP30DA029926 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2011 to 2026
$21.5M
BREATHE FREE: Smartphone Videogame-Based Incentives for Smoking CessationR44DA036252 · NIDA · ENTERTAINMENT SCIENCE PLAYMATICS, JV · PI RAIFF, BETHANY R, RAPOZA, DARION · 2014 to 2016
$1.4M
NIDA NIH HHS P30 DA029926NIDA NIH HHS R44 DA036252
6 · The paper itself

Abstract

backgroundCigarette smoking results in an estimated seven million deaths annually. Almost half of all smokers attempt to quit each year, yet only approximately 6% are successful. Although there are multiple effective interventions that can increase these odds, substantial room remains for improvement. One effective approach to helping smokers quit is contingency management, where quitting is incentivized with the delivery of monetary rewards in exchange for objective evidence (eg, exhaled carbon monoxide levels) of abstinence.

objectiveWe assessed the feasibility and promise of Inspired, a contingency management mobile app for smoking cessation that uses game-based rewards to incentivize abstinence from smoking instead of the monetary (or material) rewards typically used. We sought participant feedback and limited objective data on: the features and design of Inspired, interest in using Inspired when it becomes available, the likelihood of Inspired being an effective cessation aid, and the rank order preference of Inspired relative to other familiar smoking cessation aids.

methodsTwenty-eight treatment-seeking smokers participated in this study. Participants attended a single one-hour session in which they received an overview of the goals of the Inspired mobile game, practiced submitting breath carbon monoxide (CO) samples, and played representative levels of the game. Participants were then told that they could play an extra level, or they could stop, complete an outcome survey, receive payment, and be dismissed. A sign-up sheet requesting personal contact information was available for those who wished to be notified when the full version of Inspired becomes available.

resultsUsing binary criteria for endorsement, participants indicated that, assuming it was currently available and fully developed, they would be more likely to use Inspired than: any other smoking cessation aid (21/28, 75%), the nicotine patch (23/28, 82%), a drug designed to reduce smoking cravings (23/28, 82%), or a program involving attendance in training sessions or support group meetings (27/28, 96%). In the questionnaire, participants indicated that both the Inspired program (26/28, 93%) and the Inspired game would be "Fun" (28/28, 100%), and 71% (20/28) reported that the program would help them personally quit smoking. Fifty-eight percent of participants (15/26) chose to continue playing the game rather than immediately collecting payment for participation and leaving. Eighty-two percent of participants (23/28) signed up to be notified when the full version of Inspired becomes available.

conclusionsThis was the first study to evaluate a game-based contingency management app that uses game-based virtual goods as rewards for smoking abstinence. The outcomes suggest that the completed app has potential to be an effective smoking cessation aid that would be widely adopted by smokers wishing to quit.

Indexed as

carbon monoxidecontingency managementdigital gameshealth gamesincentivesmobile appssmokingsmoking cessationvideo gamesvirtual rewards

Identifiers

PMID29880466
PMCPMC6013711

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.