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Mobile App Usage Patterns of Patients Prescribed a Smoking Cessation Medicine: Prospective Observational Study.

ABSTRACT: Cigarette smoking is the leading preventable cause of death and is responsible for more than 480,000 deaths per year in the United States. Smoking cessation is challenging for many patients. Regardless of available treatment options, most quit attempts are unaided, and it takes multiple attempts before a patient is successful. With the ever-increasing use of smartphones, mobile apps hold promise in supporting cessation efforts. This study evaluates the ease of use and user satisfaction with the Pfizer Meds app to support smoking cessation among patients prescribed varenicline (Chantix).Study participants included varenicline users who downloaded and used the app on their personal smartphone. The main objectives were to report mobile app download frequency and usage details and to describe the participant-reported satisfaction with and usefulness of the app over the 14-week follow-up study period.Adults aged 18 years or older who had been prescribed varenicline were identified from the Express Scripts Incorporated pharmacy claims database. After meeting privacy restrictions, subjects were sent an invitation letter and second reminder letter with instructions on how to download the Pfizer Meds mobile app. Participants received a push notification to complete a smartphone-enabled survey regarding the utility of the app 12 weeks after downloading the app. Descriptive statistics summarized sociodemographics, use of varenicline, and details of use and satisfaction with the mobile app.Of the 38,129 varenicline users who were sent invitation letters, 1281 participants (3.35%) downloaded the Pfizer Meds app. Of the 1032 users with demographic and other data, 585 (56.68%) were females, and 446 (43.22%) were males; mean age was 46.4 years (SD 10.8). The mean number of app sessions per participant was 4.0 (SD 6.8). The end-of-study survey was completed by 131 survey respondents (10.23%, 131/1281); a large number of participants (117/131, 89.3%) reported being extremely, very, or moderately satisfied with the app. A total of 97 survey respondents (97/131, 74.0%) reported setting up a quit date in the app. Of those, 74 (74/97, 76%) reported quitting on their quit date.Positive patient engagement was observed in this study based on app download and usage. This study quantified how the Pfizer Meds app performed in an observational real-world data setting. The findings demonstrate the willingness of participants to set a quit date and use the app for support in medication adherence, refill reminders, and information regarding how to take the medication. This study provides real-world evidence of the contribution apps can make to the continued encouragement of smokers to improve their health by smoking cessation.

SUBMITTER: Bruno M

PROVIDER: S-EPMC5930175 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Mobile App Usage Patterns of Patients Prescribed a Smoking Cessation Medicine: Prospective Observational Study.

Bruno Marianna M Wright Marcia M Baker Christine L CL Emir Birol B Carda Eric E Clausen Michelle M Sigler Catherine C Patel Aanal A

JMIR mHealth and uHealth 20180417 4

<h4>Background</h4>Cigarette smoking is the leading preventable cause of death and is responsible for more than 480,000 deaths per year in the United States. Smoking cessation is challenging for many patients. Regardless of available treatment options, most quit attempts are unaided, and it takes multiple attempts before a patient is successful. With the ever-increasing use of smartphones, mobile apps hold promise in supporting cessation efforts. This study evaluates the ease of use and user sat ...[more]

PMID: 29666043

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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:BackgroundSmoking cessation smartphone apps have emerged as highly accessible tools to support smoking cessation efforts. It is unknown how specific app features contribute to user engagement over time and relate to smoking outcomes.ObjectiveTo provide a feature-level analysis of the Smiling Instead of Smoking app (version 2) and to link feature use to subsequent smoking cessation.MethodsNondaily smokers (N=100) used the app for a period of 49 days (1 week before quitting and 6 weeks after quitting). Participants self-reported 30-day point-prevalence abstinence at the end of this period and at a 6-month follow up (the survey response rate was 94% and 89% at these points, respectively). Self-reported 30-day point prevalence abstinence rates were 40% at the end of treatment and 56% at the 6-month follow up. The app engaged users in both positive psychology content and traditional behavioral smoking cessation content. The app sent push notifications to prompt participants to complete prescribed content (ie, a "happiness exercise" every day and a "behavioral challenge" to use the app's smoking cessation tools on 15 out of 49 days). Actions that participants took within the app were timestamped and recorded.ResultsParticipants used the app on 24.7 (SD 13.8) days out of the 49 prescribed days, interacting with the happiness content on more days than the smoking content (23.8, SD 13.8 days vs 17.8, SD 10.3 days; t99=9.28 [2-tailed]; P<.001). The prescribed content was frequently completed (45% of happiness exercises; 57% of behavioral challenges) and ad libitum tools were used on ≤7 days. Most participants used each ad libitum smoking cessation tool at least once, with higher use of personalized content (≥92% used "strategies," "cigarette log," "smoke alarms," and "personal reasons") than purely didactic content (79% viewed "benefits of quitting smoking"). The number of days participants used the app significantly predicted 30-day point-prevalence abstinence at the end of treatment (odds ratio [OR] 1.05, 95% CI 1.02-1.09; P=.002) and at the 6-month follow up (OR 1.04, 95% CI 1.008-1.07; P=.01). The number of days participants engaged with the happiness content significantly predicted smoking abstinence at the end of treatment (OR 1.05, 95% CI 1.02-1.08; P=.002) and at the 6-month follow up (OR 1.04, 95% CI 1.007-1.07; P=.02). This effect was not significant for the number of days participants engaged with the smoking cessation content of the app, either at the end of treatment (OR 1.04, 95% CI 0.996-1.08, P=.08) or at the 6-month follow up (OR 1.02, 95% CI 0.98-1.06; P=.29).ConclusionsGreater app usage predicted greater odds of self-reported 30-day point-prevalence abstinence at both the end of treatment and over the long term, suggesting that the app had a therapeutic benefit. Positive psychology content and prescriptive clarity may promote sustained app engagement over time.Trial registrationClinicalTrials.gov NCT03951766; https://clinicaltrials.gov/ct2/show/NCT03951766.

Project description:BackgroundA major cause of lapse and relapse to smoking during a quit attempt is craving triggered by cues from a smoker's immediate environment. To help smokers address these cue-induced cravings when attempting to quit, we have developed a context-aware smoking cessation app, Q Sense, which uses a smoking episode-reporting system combined with location sensing and geofencing to tailor support content and trigger support delivery in real time.ObjectiveWe sought to (1) assess smokers' compliance with reporting their smoking in real time and identify reasons for noncompliance, (2) assess the app's accuracy in identifying user-specific high-risk locations for smoking, (3) explore the feasibility and user perspective of geofence-triggered support, and (4) identify any technological issues or privacy concerns.MethodsAn explanatory sequential mixed-methods design was used, where data collected by the app informed semistructured interviews. Participants were smokers who owned an Android mobile phone and were willing to set a quit date within one month (N=15). App data included smoking reports with context information and geolocation, end-of-day (EoD) surveys of smoking beliefs and behavior, support message ratings, and app interaction data. Interviews were undertaken and analyzed thematically (N=13). Quantitative and qualitative data were analyzed separately and findings presented sequentially.ResultsOut of 15 participants, 3 (20%) discontinued use of the app prematurely. Pre-quit date, the mean number of smoking reports received was 37.8 (SD 21.2) per participant, or 2.0 (SD 2.2) per day per participant. EoD surveys indicated that participants underreported smoking on at least 56.2% of days. Geolocation was collected in 97.0% of smoking reports with a mean accuracy of 31.6 (SD 16.8) meters. A total of 5 out of 9 (56%) eligible participants received geofence-triggered support. Interaction data indicated that 50.0% (137/274) of geofence-triggered message notifications were tapped within 30 minutes of being generated, resulting in delivery of a support message, and 78.2% (158/202) of delivered messages were rated by participants. Qualitative findings identified multiple reasons for noncompliance in reporting smoking, most notably due to environmental constraints and forgetting. Participants verified the app's identification of their smoking locations, were largely positive about the value of geofence-triggered support, and had no privacy concerns about the data collected by the app.ConclusionsUser-initiated self-report is feasible for training a cessation app about an individual's smoking behavior, although underreporting is likely. Geofencing was a reliable and accurate method of identifying smoking locations, and geofence-triggered support was regarded positively by participants.

Project description:ObjectiveMobile phone-based interventions have been proven to be effective tools for smoking cessation, at least in the short term. Gamification, that is, the use of game-design elements in a non-game context, has been associated with increased engagement and motivation, critical success factors for long-term success of mobile Health solutions. However, to date, no app review has examined the use of gamification in smoking cessation mobile apps. Our review aims to examine and quantify the use of gamification strategies (broad principles) and tactics (on-screen features) among existing mobile apps for smoking cessation in the UK.MethodsThe UK Android and iOS markets were searched in February 2018 to identify smoking cessation apps. 125 Android and 15 iOS apps were tested independently by two reviewers for primary functionalities, adherence to Five A smoking cessation guidelines, and adoption of gamification strategies and tactics. We examined differences between platforms with χ2 tests. Correlation coefficients were calculated to explore the relationship between adherence to guidelines and gamification.ResultsThe most common functionality of the 140 mobile apps we reviewed allowed users to track the days since/until the quit date (86.4%). The most popular gamification strategy across both platforms was performance feedback (91.4%). The majority of apps adopted a medium level of gamification strategies (55.0%) and tactics (64.3%). Few adopted high levels of gamification strategies (6.4%) or tactics (5.0%). No statistically significant differences between the two platforms were found regarding level of gamification (p>0.05) and weak correlations were found between adherence to Five A's and gamification strategies (r=0.38) and tactics (r=0.26).ConclusionThe findings of this review show that a high level of gamification is adopted by a small minority of smoking cessation apps in the UK. Further exploration of the use of gamification in smoking cessation apps may provide insights into its role in smoking cessation.

Project description:BACKGROUND:Smoking is one of the most significant factors contributing to low life expectancy, health inequalities, and illness at the worldwide scale. Smoking cessation attempts benefit from social support. Mobile phones have changed the way we communicate through the use of freely available message-oriented apps. Mobile app-based interventions for smoking cessation programs can provide interactive, supportive, and individually tailored interventions. OBJECTIVE:This study aimed to identify emotions, coping strategies, beliefs, values, and cognitive evaluations of smokers who are in the process of quitting, and to analyze online social support provided through the analysis of messages posted to a chat function integrated into a mobile app. METHODS:In this descriptive qualitative study, informants were smokers who participated in the chat of Tobbstop. The technique to generate information was documentary through messages collected from September 2014 through June 2016, specifically designed to support a smoking cessation intervention. A thematic content analysis of the messages applied 2 conceptual models: the Lazarus and Folkman model to assess participant's experiences and perceptions and the Cutrona model to evaluate online social support. RESULTS:During the study period, 11,788 text messages were posted to the chat by 101 users. The most frequent messages offered information and emotional support, and all the basic emotions were reported in the chat. The 3 most frequent coping strategies identified were physical activity, different types of treatment such as nicotine replacement, and humor. Beliefs about quitting smoking included the inevitability of weight gain and the notion that not using any type of medications is better for smoking cessation. Health and family were the values more frequently described, followed by freedom. A smoke-free environment was perceived as important to successful smoking cessation. The social support group that was developed with the app offered mainly emotional and informational support. CONCLUSIONS:Our analysis suggests that a chat integrated into a mobile app focused on supporting smoking cessation provides a useful tool for smokers who are in the process of quitting, by offering social support and a space to share concerns, information, or strategies.

Project description:BackgroundLittle is known about how individuals engage with electronic health (eHealth) interventions over time and whether this engagement predicts health outcomes.ObjectiveThe objectives of this study, by using the example of a specific type of eHealth intervention (ie, websites for smoking cessation), were to determine (1) distinct groups of log-in trajectories over a 12-month period, (2) their association with smoking cessation, and (3) baseline user characteristics that predict trajectory group membership.MethodsWe conducted a functional clustering analysis of 365 consecutive days of log-in data from both arms of a large (N=2637) randomized trial of 2 website interventions for smoking cessation (WebQuit and Smokefree), with a primary outcome of 30-day point prevalence smoking abstinence at 12 months. We conducted analyses for each website separately.ResultsA total of 3 distinct trajectory groups emerged for each website. For WebQuit, participants were clustered into 3 groups: 1-week users (682/1240, 55.00% of the sample), 5-week users (399/1240, 32.18%), and 52-week users (159/1240, 12.82%). Compared with the 1-week users, the 5- and 52-week users had 57% higher odds (odds ratio [OR] 1.57, 95% CI 1.13-2.17; P=.007) and 124% higher odds (OR 2.24, 95% CI 1.45-3.43; P<.001), respectively, of being abstinent at 12 months. Smokefree users were clustered into 3 groups: 1-week users (645/1309, 49.27% of the sample), 4-week users (395/1309, 30.18%), and 5-week users (269/1309, 20.55%). Compared with the 1-week users, 5-week users (but not 4-week users; P=.99) had 48% higher odds (OR 1.48, 95% CI 1.05-2.07; P=.02) of being abstinent at 12 months. In general, the WebQuit intervention had a greater number of weekly log-ins within each of the 3 trajectory groups as compared with those of the Smokefree intervention. Baseline characteristics associated with trajectory group membership varied between websites.ConclusionsPatterns of 1-, 4-, and 5-week usage of websites may be common for how people engage in eHealth interventions. The 5-week usage of either website, and 52-week usage only of WebQuit, predicted a higher odds of quitting smoking. Strategies to increase eHealth intervention engagement for 4 more weeks (ie, from 1 week to 5 weeks) could be highly cost effective.Trial registrationClinicalTrials.gov NCT01812278; https://www.clinicaltrials.gov/ct2/show/NCT01812278 (Archived by WebCite at http://www.webcitation.org/6yPO2OIKR).

Project description:BACKGROUND:Smoking is considered the main cause of preventable illness and early deaths worldwide. The treatment usually prescribed to people who wish to quit smoking is a multidisciplinary intervention, combining both psychological advice and pharmacological therapy, since the application of both strategies significantly increases the chance of success in a quit attempt. OBJECTIVE:We present a study protocol of a 12-month randomized open-label parallel-group trial whose primary objective is to analyze the efficacy and efficiency of usual psychopharmacological therapy plus the Social-Local-Mobile app (intervention group) applied to the smoking cessation process compared with usual psychopharmacological therapy alone (control group). METHODS:The target population consists of adult smokers (both male and female) attending the Smoking Cessation Unit at Virgen del Rocío University Hospital, Seville, Spain. Social-Local-Mobile is an innovative intervention based on mobile technologies and their capacity to trigger behavioral changes. The app is a complement to pharmacological therapies to quit smoking by providing personalized motivational messages, physical activity monitoring, lifestyle advice, and distractions (minigames) to help overcome cravings. Usual pharmacological therapy consists of bupropion (Zyntabac 150 mg) or varenicline (Champix 0.5 mg or 1 mg). The main outcomes will be (1) the smoking abstinence rate at 1 year measured by means of exhaled carbon monoxide and urinary cotinine tests, and (2) the result of the cost-effectiveness analysis, which will be expressed in terms of an incremental cost-effectiveness ratio. Secondary outcome measures will be (1) analysis of the safety of pharmacological therapy, (2) analysis of the health-related quality of life of patients, and (3) monitoring of healthy lifestyle and physical exercise habits. RESULTS:Of 548 patients identified using the hospital's electronic records system, we excluded 308 patients: 188 declined to participate and 120 did not meet the inclusion criteria. A total of 240 patients were enrolled: the control group (n=120) will receive usual psychopharmacological therapy, while the intervention group (n=120) will receive usual psychopharmacological therapy plus the So-Lo-Mo app. The project was approved for funding in June 2015. Enrollment started in October 2016 and was completed in October 2017. Data gathering was completed in November 2018, and data analysis is under way. The first results are expected to be submitted for publication in early 2019. CONCLUSIONS:Social networks and mobile technologies influence our daily lives and, therefore, may influence our smoking habits as well. As part of the SmokeFreeBrain H2020 European Commission project, this study aims at elucidating the potential role of these technologies when used as an extra aid to quit smoking. TRIAL REGISTRATION:ClinicalTrials.gov NCT03553173; https://clinicaltrials.gov/ct2/show/record/NCT03553173 (Archived by WebCite at http://www.webcitation.org/74DuHypOW). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):PRR1-10.2196/12464.

Dataset Information

Mobile App Usage Patterns of Patients Prescribed a Smoking Cessation Medicine: Prospective Observational Study.

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Mobile App Usage Patterns of Patients Prescribed a Smoking Cessation Medicine: Prospective Observational Study.

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