Evaluation of the Tobbstop Mobile App for Smoking Cessation: Cluster Randomized Controlled Clinical Trial

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Abstract

Background

Mobile apps provide an accessible way to test new health-related methodologies. Tobacco is still the primary preventable cause of death in industrialized countries, constituting an important public health issue. New technologies provide novel opportunities that are effective in the cessation of smoking tobacco.

Objective

This paper aims to evaluate the efficacy and usage of a mobile app for assisting adult smokers to quit smoking.

Methods

We conducted a cluster randomized clinical trial. We included smokers older than 18 years who were motivated to stop smoking and used a mobile phone compatible with our mobile app. We carried out follow-up visits at 15, 30, and 45 days, and at 2, 3, 6, and 12 months. Participants of the intervention group had access to the Tobbstop mobile app designed by the research team. The primary outcomes were continuous smoking abstinence at 3 and 12 months.

Results

A total of 773 participants were included in the trial, of which 602 (77.9%) began the study on their D-Day. Of participants in the intervention group, 34.15% (97/284) did not use the app. The continuous abstention level was significantly larger in the intervention group participants who used the app than in those who did not use the app at both 3 months (72/187, 38.5% vs 13/97, 13.4%; P<.001) and 12 months (39/187, 20.9% vs 8/97, 8.25%; P=.01). Participants in the intervention group who used the app regularly and correctly had a higher probability of not being smokers at 12 months (OR 7.20, 95% CI 2.14-24.20; P=.001) than the participants of the CG.

Conclusions

Regular use of an app for smoking cessation is effective in comparison with standard clinical practice.

Trial Registration

Clinicaltrials.gov NCT01734421; https://clinicaltrials.gov/ct2/show/NCT01734421

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Most cited references 15

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Who Uses Mobile Phone Health Apps and Does Use Matter? A Secondary Data Analytics Approach

Jennifer K Carroll, Anne S. Moorhead, Raymond R Bond … (2017)

Background Mobile phone use and the adoption of healthy lifestyle software apps (“health apps”) are rapidly proliferating. There is limited information on the users of health apps in terms of their social demographic and health characteristics, intentions to change, and actual health behaviors. Objective The objectives of our study were to (1) to describe the sociodemographic characteristics associated with health app use in a recent US nationally representative sample; (2) to assess the attitudinal and behavioral predictors of the use of health apps for health promotion; and (3) to examine the association between the use of health-related apps and meeting the recommended guidelines for fruit and vegetable intake and physical activity. Methods Data on users of mobile devices and health apps were analyzed from the National Cancer Institute’s 2015 Health Information National Trends Survey (HINTS), which was designed to provide nationally representative estimates for health information in the United States and is publicly available on the Internet. We used multivariable logistic regression models to assess sociodemographic predictors of mobile device and health app use and examine the associations between app use, intentions to change behavior, and actual behavioral change for fruit and vegetable consumption, physical activity, and weight loss. Results From the 3677 total HINTS respondents, older individuals (45-64 years, odds ratio, OR 0.56, 95% CI 0.47-68; 65+ years, OR 0.19, 95% CI 0.14-0.24), males (OR 0.80, 95% CI 0.66-0.94), and having degree (OR 2.83, 95% CI 2.18-3.70) or less than high school education (OR 0.43, 95% CI 0.24-0.72) were all significantly associated with a reduced likelihood of having adopted health apps. Similarly, both age and education were significant variables for predicting whether a person had adopted a mobile device, especially if that person was a college graduate (OR 3.30). Individuals with apps were significantly more likely to report intentions to improve fruit (63.8% with apps vs 58.5% without apps, P=.01) and vegetable (74.9% vs 64.3%, P<.01) consumption, physical activity (83.0% vs 65.4%, P<.01), and weight loss (83.4% vs 71.8%, P<.01). Individuals with apps were also more likely to meet recommendations for physical activity compared with those without a device or health apps (56.2% with apps vs 47.8% without apps, P<.01). Conclusions The main users of health apps were individuals who were younger, had more education, reported excellent health, and had a higher income. Although differences persist for gender, age, and educational attainment, many individual sociodemographic factors are becoming less potent in influencing engagement with mobile devices and health app use. App use was associated with intentions to change diet and physical activity and meeting physical activity recommendations.

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Can Smartphone Apps Increase Physical Activity? Systematic Review and Meta-Analysis

Amelia Romeo, Sarah Edney, Ronald Plotnikoff … (2019)

Background Smartphone apps are a promising tool for delivering accessible and appealing physical activity interventions. Given the large growth of research in this field, there are now enough studies using the “gold standard” of experimental design—the randomized controlled trial design—and employing objective measurements of physical activity, to support a meta-analysis of these scientifically rigorous studies. Objective This systematic review and meta-analysis aimed to determine the effectiveness of smartphone apps for increasing objectively measured physical activity in adults. Methods A total of 7 electronic databases (EMBASE, EmCare, MEDLINE, Scopus, Sport Discus, The Cochrane Library, and Web of Science) were searched from 2007 to January 2018. Following the Population, Intervention, Comparator, Outcome and Study Design format, studies were eligible if they were randomized controlled trials involving adults, used a smartphone app as the primary or sole component of the physical activity intervention, used a no- or minimal-intervention control condition, and measured objective physical activity either in the form of moderate-to-vigorous physical activity minutes or steps. Study quality was assessed using a 25-item tool based on the Consolidated Standards of Reporting Trials checklist. A meta-analysis of study effects was conducted using a random effects model approach. Sensitivity analyses were conducted to examine whether intervention effectiveness differed on the basis of intervention length, target behavior (physical activity alone vs physical activity in combination with other health behaviors), or target population (general adult population vs specific health populations). Results Following removal of duplicates, a total of 6170 studies were identified from the original database searches. Of these, 9 studies, involving a total of 1740 participants, met eligibility criteria. Of these, 6 studies could be included in a meta-analysis of the effects of physical activity apps on steps per day. In comparison with the control conditions, smartphone apps produced a nonsignificant (P=.19) increase in participants’ average steps per day, with a mean difference of 476.75 steps per day (95% CI −229.57 to 1183.07) between groups. Sensitivity analyses suggested that physical activity programs with a duration of less than 3 months were more effective than apps evaluated across more than 3 months (P=.01), and that physical activity apps that targeted physical activity in isolation were more effective than apps that targeted physical activity in combination with diet (P=.04). Physical activity app effectiveness did not appear to differ on the basis of target population. Conclusions This meta-analysis provides modest evidence supporting the effectiveness of smartphone apps to increase physical activity. To date, apps have been most effective in the short term (eg, up to 3 months). Future research is needed to understand the time course of intervention effects and to investigate strategies to sustain intervention effects over time.

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Clickotine, A Personalized Smartphone App for Smoking Cessation: Initial Evaluation

Brian Iacoviello, Joshua Steinerman, David B Klein … (2017)

Background Tobacco smoking is the leading cause of preventable death in the United States, and the annual economic burden attributable to smoking exceeds US $300 billion. Obstacles to smoking cessation include limited access and adherence to effective cessation interventions. Technology can help overcome these obstacles; many smartphone apps have been developed to aid smoking cessation, but few that conform to the US clinical practice guideline (USCPG) have been rigorously tested and reported in the literature. Clickotine is a novel smartphone app for smoking cessation, designed to deliver the essential features of the USCPG and engineered to engage smokers by personalizing intervention components. Objective Our objective was to assess the engagement, efficacy, and safety of Clickotine in an initial, single-arm study. Outcomes measured were indicators of engagement with the smartphone app (number of app opens, number of interactions with the Clickotine program, and weeks active with Clickotine), cessation outcomes of 7- and 30-day self-reported abstinence from smoking, and negative health events. Methods We recruited US residents between 18 and 65 years of age who owned an iPhone and smoked 5 or more cigarettes daily for the study via online advertising. Respondents were prescreened for eligibility by telephone and, if appropriate, directed to a Web portal to provide informed consent, confirm eligibility, and download the Clickotine app. Participants completed study assessments via the online portal at baseline and after 8 weeks. Data were collected in Amazon S3 with no manual data entry, and access to all data was maximally restrictive, logged, and auditable. Results A total of 416 participants downloaded the app and constituted the intention-to-treat (ITT) sample. On average, participants opened the Clickotine app 100.6 times during the 8-week study (median 69), logged 214.4 interactions with the Clickotine program (median 178), and remained engaged with Clickotine for 5.3 weeks (median 5). Among the ITT sample, 45.2% (188/416) reported 7-day abstinence and 26.2% (109/416) reported 30-day abstinence from smoking after 8 weeks. Completer analysis focused on 365 (87.7%) of the 416 enrolled participants who completed the 8-week questionnaire revealed that 51.5% (188/365) of completers reported 7-day abstinence and 29.9% (109/365) reported 30-day abstinence. Few adverse events, mostly consistent with nicotine withdrawal symptoms, were reported and overall no safety signal was detected. Conclusions In this initial single-arm trial, Clickotine users appeared to demonstrate encouraging indicators of engagement in terms of the number of app opens, number of program interactions, and continued engagement over time. Clickotine users reported encouraging quit rates while reporting few adverse events. Future research is warranted to assess Clickotine’s efficacy in a randomized controlled trial. Trial Registration Clinicaltrials.gov NCT02656745; https://clinicaltrials.gov/ct2/show/NCT02656745 (Archived by WebCite at http://www.webcitation.org/6peTT4x60)

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Author and article information

Contributors

Cristina Rey-Reñones: On behalf of : Grup de Recerca Tecnologies de la Informació i Comunicació en Atenció Primària

ORCID: https://orcid.org/0000-0003-2017-8220

Institut Català de la SalutUnitat de Suport a la Recerca Camp de TarragonaC/ Camí de Riudoms, 53Reus, 43202Spain34 977778515 ext 405crey.tgn.ics@gencat.cat

Esther Granado-Font: On behalf of : TIC-AP Research Gropu (IDIAP)

ORCID: https://orcid.org/0000-0002-4484-6054

Journal

Journal ID (nlm-ta): JMIR Mhealth Uhealth

Journal ID (iso-abbrev): JMIR Mhealth Uhealth

Journal ID (publisher-id): JMU

Title: JMIR mHealth and uHealth

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Electronic): 2291-5222

Publication date Collection: June 2020

Publication date (Electronic): 26 June 2020

Volume: 8

Issue: 6

Electronic Location Identifier: e15951

Affiliations

[1 ] Unitat de Suport a la Recerca Camp de Tarragona Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina Reus Spain

[2 ] Departament de Ciències Mèdiques Bàsiques Universitat Rovira i Virgili Reus Spain

[3 ] Institut Català de la Salut Unitat de Suport a la Recerca Camp de Tarragona Reus Spain

[4 ] Equip d'Atenció Primaria La Granja (Tarragona-2) Direcció d'Atenció Primaria Camp de Tarragona Institut Català de la Salut Torreforta Spain

[5 ] Equip d'Atenció Primaria Horts de Miró (Reus-4) Direcció d'Atenció Primaria Camp de Tarragona Institut Català de la Salut Reus Spain

[6 ] Unitat d’Anàlisi i Qualitat Xarxa Sanitària i Social Santa Tecla Tarragona Spain

[7 ] Departament d’Enginyeria Informàtica i Matemàtiques Universitat Rovira i Virgili Tarragona Spain

Author notes

Corresponding Author: Cristina Rey-Reñones crey.tgn.ics@ 123456gencat.cat

Author information

Meritxell Pallejà-Millán https://orcid.org/0000-0003-1985-8894

Cristina Rey-Reñones https://orcid.org/0000-0003-2017-8220

Maria Luisa Barrera Uriarte https://orcid.org/0000-0002-7152-064X

Esther Granado-Font https://orcid.org/0000-0002-4484-6054

Josep Basora https://orcid.org/0000-0003-0278-1149

Gemma Flores-Mateo https://orcid.org/0000-0001-6901-7327

Jordi Duch https://orcid.org/0000-0003-2639-6333

Article

Publisher ID: v8i6e15951

DOI: 10.2196/15951

PMC ID: 7381259

PubMed ID: 32589153

SO-VID: d3623d89-8879-4229-9c48-1f0cbdd445d6

Copyright © ©Meritxell Pallejà-Millán, Cristina Rey-Reñones, Maria Luisa Barrera Uriarte, Esther Granado-Font, Josep Basora, Gemma Flores-Mateo, Jordi Duch. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 26.06.2020.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.

History

Date received : 9 September 2019

Date revision requested : 20 October 2019

Date revision received : 9 December 2019

Date accepted : 29 March 2020

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