Evidence map›Paper›PMID 29907557›Full record

ArticleJMIR mHealth and uHealth2018

Effective Behavioral Changes through a Digital mHealth App: Exploring the Impact of Hedonic Well-Being, Psychological Empowerment and Inspiration.

Yuting Lin, Carina Tudor-Sfetea, Sarim Siddiqui, Yusuf Sherwani, Maroof Ahmed, Andreas B Eisingerich

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
–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

45 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  6. NoFumo+: A Clinical Trial of an mHealth for Smoking Cessation with Hospitalized Patients.International journal of environmental research and public health · 2021
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  14. Mobile Health Interventions for Adolescent Smoking Prevention: A Scoping Review.Asian Pacific journal of cancer prevention : APJCP · 2026
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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

6 authors.

Yuting Lin *Imperial College Business School, Imperial College London, London, United Kingdom.ORCID http://orcid.org/0000-0002-1920-3989
Carina Tudor-SfeteaDigital Therapeutics, Inc, London, United Kingdom.ORCID http://orcid.org/0000-0002-5494-4731
Sarim SiddiquiDigital Therapeutics, Inc, London, United Kingdom.ORCID http://orcid.org/0000-0002-4909-316X
Yusuf SherwaniDigital Therapeutics, Inc, London, United Kingdom.ORCID http://orcid.org/0000-0002-2027-9550
Maroof AhmedDigital Therapeutics, Inc, London, United Kingdom.ORCID http://orcid.org/0000-0003-1057-6583
Andreas B Eisingerich *Imperial College Business School, Imperial College London, London, United Kingdom.ORCID http://orcid.org/0000-0001-5531-4662

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNew mobile health (mHealth) software apps are emerging and are providing the foundation to radically transform the practice and reach of medical research and care. For this study we collaborated with Quit Genius, a cognitive behavioral therapy (CBT) based mHealth app that helps users quit smoking, to explore the effective design of a digital mHealth app; one that delivers important benefits to its users and helps them change their behaviors for a healthier lifestyle.

objectiveThe specific aims of this study were to (1) explore the key role of CBT program progress, (2) examine the gamification design app elements that deliver significant benefits (ie, empowerment, well-being, inspiration) to users, (3) explore the effectiveness of these app elements to help users quit smoking or reduce the number of cigarettes smoked, and (4) identify and describe any potential drivers and hindrances arising from the app design elements.

methodsWe developed an online survey and sent an email invitation to 4144 individuals, who had previously or were at the time using the Quit Genius mHealth app, to encourage participation in the study. We matched the online survey data with objective app usage data of the study participants.

resultsA dataset of 190 completed responses was used. At the time of the survey, respondents had completed an average of 60% of the CBT program in the Quit Genius mHealth app. Of the respondents, 36.3% (69/190) noted to have quit smoking successfully after using the Quit Genius app. As for those who remained smokers after using the app (N=121), the number of cigarettes smoked per day was significantly reduced by 59.6%. The ability of the app to enhance users' hedonic well-being and psychologically empower them in their daily lives was identified as being key in helping users quit smoking. Specifically, the results show that users whose well-being was enhanced through the app were 1.72 times more likely to quit smoking successfully. Moreover, a one-unit increase on a 7-point Likert scale in the app's ability to empower smokers in their daily lives led to a reduction of cigarettes smoked per day of 53%. The app's inspiration to users, however, was negatively associated with quitting success and the reduction in cigarette smoked per day.

conclusionsThe findings offer important insights for the effective design of digital mHealth apps. Specifically, we find that perceived psychological empowerment and enhanced hedonic well-being from the mobile solution may be a more impactful way to support the effectiveness of mobile cognitive behavioral therapy for smoking cessation than eliciting strong inspiration.

Indexed as

behavior change and preventioncognitive behavioral therapydigitalempowermentgamificationinspirationmHealthmobile appwell-being

Identifiers

PMID29907557
PMCPMC6026304

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.