Evidence map›Paper›PMID 33929336›Full record

ArticleJMIR mHealth and uHealth2021

Self-Efficacy and Motivation to Quit of Smokers Seeking to Quit: Quantitative Assessment of Smoking Cessation Mobile Apps.

Nikita B Rajani, Nikolaos Mastellos, Filippos T Filippidis

Registry-linked trialAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05318651 (Determinants of Use of Mobile Apps for Smoking Cessation), which is not on this map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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.

NCT05318651 nacompletednot on this mapstarted 2022, after this paper: background citation

Determinants of Use of Mobile Apps for Smoking Cessation

TypeinterventionalSponsorParis Nanterre UniversityRan2022 to 2022Enrolled255ConditionsSmoking Cessation, Technology Acceptance Model, CBT, EngagementArmsKwit SAS - smoking cessation app
3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

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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

3 authors.

Nikita B RajaniDepartment of Primary Care and Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0001-6016-6705
Nikolaos MastellosDepartment of Primary Care and Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0003-4573-3657
Filippos T FilippidisDepartment of Primary Care and Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-2101-2559

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDecreasing trends in the number of individuals accessing face-to-face support are leaving a significant gap in the treatment options for smokers seeking to quit. Face-to-face behavioral support and other interventions attempt to target psychological factors such as the self-efficacy and motivation to quit of smokers, as these factors are associated with an increased likelihood of making quit attempts and successfully quitting. Although digital interventions, such as smoking cessation mobile apps, could provide a promising avenue to bridge the growing treatment gap, little is known about their impact on psychological factors that are vital for smoking cessation.

objectiveThis study aims to better understand the possible impact of smoking cessation mobile apps on important factors for successful cessation, such as self-efficacy and motivation to quit. Our aim is to assess the self-efficacy and motivation to quit levels of smokers before and after the use of smoking cessation mobile apps.

methodsSmokers seeking to quit were recruited to participate in a 4-week app-based study. After screening, eligible participants were asked to use a mobile app (Kwit or Quit Genius). The smoking self-efficacy questionnaire and the motivation to stop smoking scale were used to measure the self-efficacy and motivation to quit, respectively. Both were assessed at baseline (before app use), midstudy (2 weeks after app use), and end-study (4 weeks after app use). Paired sample two-tailed t tests were used to investigate whether differences in self-efficacy and motivation between study time points were statistically significant. Linear regression models investigated associations between change in self-efficacy and change in motivation to quit before and after app use with age, gender, and nicotine dependence.

resultsA total of 116 participants completed the study, with the majority being male (71/116, 61.2%), employed (76/116, 65.6%), single (77/116, 66.4%), and highly educated (87/116, 75.0%). A large proportion of participants had a low to moderate dependence on nicotine (107/116, 92.2%). A statistically significant increase of 5.09 points (95% CI 1.83-8.34) from 37.38 points at baseline in self-efficacy was found at the end of the study. Statistically significant increases were also found for the subcomponents of self-efficacy (intrinsic and extrinsic self-efficacies). Similarly, a statistically significant increase of 0.38 points (95% CI 0.06-0.70) from 5.94 points at baseline in motivation to quit was found at the end of the study. Gender, age, and nicotine dependence were not statistically significantly associated with changes in self-efficacy and motivation to quit.

conclusionsThe assessed mobile apps positively impacted the self-efficacy and motivation to quit of smokers making quit attempts. This has important implications on the possible future use of digitalized interventions and how they could influence important psychological factors for quitting such as self-efficacy and motivation. However, further research is needed to assess whether digital interventions can supplement or replace traditional forms of therapy.

Indexed as

Mobile ApplicationsSmoking CessationHumansMaleMotivationSelf EfficacySmokersSurveys and QuestionnairesmHealthmobile applicationsmobile phonemotivation to quitself-efficacysmoking cessation

Identifiers

PMID33929336
PMCPMC8122290

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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.