Dataset Information

A comparison of the characteristics of iOS and Android users of a smoking cessation app.

ABSTRACT: iOS and Android smartphone users may differ in ways that affect their use and likelihood of success when using a smoking cessation application (app). If so, it may be necessary to take the device type (iOS and Android) into account when designing smoking cessation apps and in studies evaluating app effectiveness. How do socio-demographic and smoking characteristics, potentially relevant to engagement and cessation outcomes, of the SF28 app users differ between those using the iOS version and those using the Android version? Data were collected between October 2013 and April 2015. The variables measured were age, gender, social grade, time since the most recent quit attempt, choice of medication use (nicotine replacement therapy or varenicline), weekly expenditure on cigarettes, cigarettes smoked per day, reason for using the app and quit date set. The alpha was set to p < 0.006 to adjust for multiple comparisons. A total of 1368 users were included in the analysis. iOS and Android device users were similar in terms of age, social grade, weekly expenditure on cigarettes and cigarettes smoked per day. Compared with Android users, iOS users were more likely to have downloaded the app for a serious quit attempt (74.3 versus 69.6%, p = 0.001), made a quit attempt within the last 12 months (59.6 versus 45.9%, p < 0.001) and set their quit date on the day of registration (61 versus 46.2%, p < 0.001). They were less likely to have used stop-smoking medication to support their quit attempt (31.5 versus 48.6%, p < 0.001). Differences between smokers using the iOS version of smoking cessation apps and those using the Android version may influence quit success.

SUBMITTER: Ubhi HK

PROVIDER: S-EPMC5526810 | biostudies-other | 2017 Jun

REPOSITORIES: biostudies-other

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Project description:BackgroundThe number of mobile apps that support smoking cessation is growing, indicating the potential of the mobile phone as a means to support cessation. Knowledge about the potential end users for cessation apps results in suggestions to target potential user groups in a dissemination strategy, leading to a possible increase in the satisfaction and adherence of cessation apps.ObjectiveThis study aimed to characterize potential end users for a specific mobile health (mHealth) smoking cessation app.MethodsA quantitative study was conducted among 955 Dutch smokers and ex-smokers. The respondents were primarily recruited from addiction care facilities and hospitals through Web-based media via websites and forums. The respondents were surveyed on their demographics, smoking behavior, and personal innovativeness. The intention to use and the attitude toward a cessation app were determined on a 5-point Likert scale. To study the association between the characteristics and intention to use and attitude, univariate and multivariate ordinal logistic regression analyses were performed.ResultsThe multivariate ordinal logistic regression showed that the number of previous quit attempts (odds ratio [OR] 4.1, 95% CI 2.4-7.0, and OR 3.5, 95% CI 2.0-5.9) and the score on the Fagerstrom Test of Nicotine Dependence (OR 0.8, 95% CI 0.8-0.9, and OR 0.8, 95% CI 0.8-0.9) positively correlates with the intention to use a cessation app and the attitude toward cessation apps, respectively. Personal innovativeness also positively correlates with the intention to use (OR 0.3, 95% CI 0.2-0.4) and the attitude towards (OR 0.2, 95% CI 0.1-0.4) a cessation app. No associations between demographics and the intention to use or the attitude toward using a cessation app were observed.ConclusionsThis study is among the first to show that demographic characteristics such as age and level of education are not associated with the intention to use and the attitude toward using a cessation app when characteristics related specifically to the app, such as nicotine dependency and the number of quit attempts, are present in a multivariate regression model. This study shows that the use of mHealth apps depends on characteristics related to the content of the app rather than general user characteristics.

Project description:BackgroundHeated tobacco products (HTPs) are widespread in Japan, and smoking cessation of such products has become an important issue owing to the spread of harmful effects from HTPs. The efficacy of online digital therapy has been reported in smoking cessation treatment; however, we have limited evidence of online smoking cessation programs for HTP users.ObjectiveIn this study, we evaluate the usefulness of the Ascure program for HTP users (defined as exclusive HTP use or dual use of HTP and cigarettes) compared with exclusive cigarette users.MethodsThis was a retrospective study. We recruited adult smokers participating in the Ascure online smoking cessation program in Japan from June 2019 to February 2021. The Ascure smartphone app provided four elements: (1) educational video tutorials to enhance the understanding of nicotine dependence, (2) a personalized to-do list for behavior change, (3) a digital diary for record keeping, and (4) interactive chat sessions for relief from cravings or withdrawal symptoms. The primary outcome was the continuous abstinence rate (CAR) at weeks 21 to 24, biochemically validated using salivary cotinine testing. We considered those who dropped out of the program as smoking cessation failures. We analyzed the primary outcome using inverse probability weighting against tobacco product type estimated by multinomial propensity scores. We also assessed CAR at weeks 9 to 12 and program adherence.ResultsWe analyzed data from 2952 participants, including 52% (1524/3478) in the cigarette group, 35% (1038/3478) in the HTP group, and 13% (390/3478) in the dual-use group, who had a mean age of 43.4 (SD 10.8) years and included 17% (513/2952) women. CAR at weeks 21 to 24 showed that exclusive HTP users were more likely to stop tobacco use than exclusive cigarette smokers (CAR 52.6% for cigarette users vs CAR 64.8% for HTP users; odds ratio [OR] 1.17, 95% CI 1.12-1.22; P<.001). There was no significant difference between the exclusive cigarette users and the dual users (CAR 52.6% for cigarette users vs CAR 48.7% for dual users; OR 0.99, 95% CI 0.93-1.05; P=.77). CAR at weeks 9 to 12 was 56.7% (95% CI 54.2%-59.2%) for the exclusive cigarette users, 68.3% (95% CI 65.5%-71.1%) for the exclusive HTP users, and 58.2% (95% CI 53.3%-63.1%) for the dual users. The program adherence rate at week 24 was 70.7% overall (68.4% for cigarette users, 75% for HTP users, and 67.9% for dual users).ConclusionsExclusive HTP users had higher CARs and adherence compared with exclusive cigarette users, indicating a higher affinity for the Ascure online smoking cessation program. This program might be a useful smoking cessation option for HTP users, as well as for cigarette smokers.

Project description:BackgroundOur prototype smoking cessation chatbot, Quin, provides evidence-based, personalized support delivered via a smartphone app to help people quit smoking. We developed Quin using a multiphase program of co-design research, part of which included focus group evaluation of Quin among stakeholders prior to clinical testing.ObjectiveThis study aimed to gather and compare feedback on the user experience of the Quin prototype from end users and smoking cessation professionals (SCPs) via a beta testing process to inform ongoing chatbot iterations and refinements.MethodsFollowing active and passive recruitment, we conducted web-based focus groups with SCPs and end users from Queensland, Australia. Participants tested the app for 1-2 weeks prior to focus group discussion and could also log conversation feedback within the app. Focus groups of SCPs were completed first to review the breadth and accuracy of information, and feedback was prioritized and implemented as major updates using Agile processes prior to end user focus groups. We categorized logged in-app feedback using content analysis and thematically analyzed focus group transcripts.ResultsIn total, 6 focus groups were completed between August 2022 and June 2023; 3 for SCPs (n=9 participants) and 3 for end users (n=7 participants). Four SCPs had previously smoked, and most end users currently smoked cigarettes (n=5), and 2 had quit smoking. The mean duration of focus groups was 58 (SD 10.9; range 46-74) minutes. We identified four major themes from focus group feedback: (1) conversation design, (2) functionality, (3) relationality and anthropomorphism, and (4) role as a smoking cessation support tool. In response to SCPs' feedback, we made two major updates to Quin between cohorts: (1) improvements to conversation flow and (2) addition of the "Moments of Crisis" conversation tree. Participant feedback also informed 17 recommendations for future smoking cessation chatbot developments.ConclusionsFeedback from end users and SCPs highlighted the importance of chatbot functionality, as this underpinned Quin's conversation design and relationality. The ready accessibility of accurate cessation information and impartial support that Quin provided was recognized as a key benefit for end users, the latter of which contributed to a feeling of accountability to the chatbot. Findings will inform the ongoing development of a mature prototype for clinical testing.

Project description:BackgroundMost smokers attempt to stop using cigarettes numerous times before successfully quitting. Cigarette cravings may undermine perceived competence to quit and thus constitute psychological threats to the individual's self-concept. Self-affirmation may promote smoking cessation by offsetting these threats.ObjectiveThis study examines whether self-affirmation is associated with smoking cessation in the context of a cessation app. Two types of self-affirmation are examined: tendency to spontaneously self-affirm, and self-affirmation inductions added to a publicly available smoking cessation app (Smoke-Free Quit Smoking Now). In addition, this study explores whether optimism and emotional states (happiness, anger, anxiousness, hopefulness, sadness) predict smoking cessation.MethodsAll users who met the inclusion criteria, provided consent to participate, and completed a baseline assessment, including all individual difference measures, were randomized to 1 of 4 conditions. Half of the participants were randomly assigned to complete a self-affirmation induction upon study entry. Orthogonally, half of the participants were randomly assigned to receive self-affirming text notifications during their quit attempt or to receive conventional notifications. The induction and the text notifications were fully automated, and all data were collected through self-assessments in the app. Self-reported smoking cessation was assessed 1 month and 3 months following study entry.ResultsThe study enrolled 7899 participants; 647 completed the 1-month follow-up. Using an intent-to-treat analysis at the 1-month follow-up, 7.2% (569/7899) of participants self-reported not smoking in the previous week and 6.4% (503/7899) self-reported not smoking in the previous month. Greater tendency to spontaneously self-affirm predicted a greater likelihood of cessation (P<.001) at 1 month after controlling for smoking-related variables. Neither self-affirmation induction influenced cessation. In addition, spontaneous self-affirmation did not moderate the relationship between self-affirmation inductions and cessation. Greater baseline sadness was associated with a lower likelihood of reporting successful cessation. Optimism predicted past-week cessation at the 1-month follow-up, and both happiness and anger predicted past-month cessation at the 1-month follow-up; however, none of these potential predictors moderated the relationship between self-affirmation conditions and successful cessation.ConclusionsSpontaneous self-affirmation may be an important psychological resource for managing threats to self-concept during the smoking cessation process. Sadness may hinder quit attempts. Future research can explicate how spontaneous versus induced self-affirmation can promote smoking cessation and examine boundary conditions for the effectiveness of disseminated self-affirmation interventions.Trial registrationISRCTN Registry 56646695; https://www.isrctn.com/ISRCTN56646695.

Project description:Background and aimsMost e-cigarette users who also smoke combustible cigarettes (dual users) begin vaping to quit smoking, yet only a subset succeeds. We hypothesized that reinforcing characteristics of e-cigarettes (vaping reinforcement) would positively predict smoking cessation propensity (SCP) among dual users.DesignSecondary analysis of cross-sectional baseline data from dual users in an ongoing smoking cessation trial. Exploratory and confirmatory factor analysis (EFA and CFA) created latent variables for vaping reinforcement and SCP. A structural equation modeling (SEM) approach was used to test the hypothesis.SettingUnited States.ParticipantsA national sample of dual users of combustible and electronic cigarettes who smoke and vape at least once per week (n = 2896) were enrolled (63% male; mean age = 29.9 years) into a randomized controlled trial in which they would receive either smoking cessation materials or no smoking cessation materials.MeasurementsVaping reinforcement was indexed by vaping frequency (days/week vaping, times/day vaping, puffs/e-cigarette use), e-cigarette characteristics [numbers of modifications and tobacco or non-tobacco flavors, nicotine content (mg) and positive e-cigarette expectancies]. SCP was measured by items of confidence, commitment to being smoke-free, cessation motivation (contemplation ladder), change in cigarettes per day since beginning e-cigarette use and negative smoking expectancies.FindingsFour factors emerged from the EFA: vaping propensity (vaping frequency, positive expectancies), vaping enthusiasm (e-cigarette modifications, using non-tobacco flavors, puffs per use), nicotine/tobacco flavor (nicotine strength, tobacco flavors) and SCP (negative expectancies about smoking, motivation to quit smoking, reduction in smoking). A CFA upheld the exploratory factor structure [root mean square error of approximation (RMSEA) = 0.046, CFI = 0.91]. An SEM with the three vaping latent variables directly predicting SCP had good model fit (RMSEA = 0.030, CFI = 0.97) with a positive relationship of vaping propensity (0.509, P < 0.001), and small negative relationships of vaping enthusiasm (-0.158, P = 0.014) and nicotine/tobacco flavor (-0.230, P < 0.001).ConclusionsAmong e-cigarette users who also smoke combustible cigarettes, frequent vaping combined with positive e-cigarette expectancies appears to predict greater smoking cessation propensity. However, vaping enthusiasm (measured by e-cigarette modifications, using non-tobacco flavors and puffs per use), higher nicotine content and use of tobacco flavored solution may reduce cessation propensity.

Project description:BackgroundTobacco 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.ObjectiveOur 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.MethodsWe 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.ResultsA 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.ConclusionsIn 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 registrationClinicaltrials.gov NCT02656745; https://clinicaltrials.gov/ct2/show/NCT02656745 (Archived by WebCite at http://www.webcitation.org/6peTT4x60).

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A comparison of the characteristics of iOS and Android users of a smoking cessation app.

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