A mobile app to aid smoking cessation: preliminary evaluation of SmokeFree28

Smartband-based smoking detection and real-time brief mindfulness intervention: findings from a feasibility clinical trial

BACKGROUND

Smartbands can be used to detect cigarette smoking and deliver real time smoking interventions. Brief mindfulness interventions have been found to reduce smoking.

OBJECTIVE

This single arm feasibility trial used a smartband to detect smoking and deliver brief mindfulness exercises.

METHODS

Daily smokers who were motivated to reduce their smoking wore a smartband for 60 days. For 21 days, the smartband monitored, detected and notified the user of smoking in real time. After 21 days, a 'mindful smoking' exercise was triggered by detected smoking. After 28 days, a 'RAIN' (recognize, allow, investigate, nonidentify) exercise was delivered to predicted smoking. Participants received mindfulness exercises by text message and online mindfulness training. Feasibility measures included treatment fidelity, adherence and acceptability.

RESULTS

Participants (N=155) were 54% female, 76% white non-Hispanic, and treatment starters (n=115) were analyzed. Treatment fidelity cutoffs were met, including for detecting smoking and delivering mindfulness exercises. Adherence was mixed, including moderate smartband use and low completion of mindfulness exercises. Acceptability was mixed, including high helpfulness ratings and mixed user experiences data. Retention of treatment starters was high (81.9%).

CONCLUSIONS

Findings demonstrate the feasibility of using a smartband to track smoking and deliver quit smoking interventions contingent on smoking.

Effectiveness of digital tools for smoking cessation in Asian countries: a systematic review

AIM

The use of tobacco is responsible for many preventable diseases and deaths worldwide. Digital interventions have greatly improved patient health and clinical care and have proven to be effective for quitting smoking in the general population due to their flexibility and potential for personalization. However, there is limited evidence on the effectiveness of digital interventions for smoking cessation in Asian countries.

METHODS

Three major databases - Web of Science (WOS), Scopus, and PubMed - for relevant studies published between 1 January 2010 and 12 February 2023 were searched for studies evaluating the effectiveness of digital intervention for smoking cessation in Asian countries.

RESULTS

A total of 25 studies of varying designs were eligible for this study collectively involving a total of n = 22,005 participants from 9 countries. Among different digital tools for smoking cessation, the highest abstinence rate (70%) was reported with cognitive behavioural theory (CBT)-based smoking cessation intervention via Facebook followed by smartphone app (60%), WhatsApp (59.9%), and Pharmacist counselling with Quit US smartphone app (58.4%). However, WhatsApp was preferred over Facebook intervention due to lower rates of relapse. WeChat was responsible for 15.6% and 41.8% 7-day point prevalence abstinence. For telephone/text messaging abstinence rate ranged from 8-44.3% and quit rates from 6.3% to 16.8%. Whereas, no significant impact of media/multimedia messages and web-based learning on smoking cessation was observed in this study.

CONCLUSION

Based on the study findings the use of digital tools can be considered an alternative and cost-effective smoking cessation intervention as compared to traditional smoking cessation interventions.

Feasibility and Engagement of a Mobile App Preparation Program (Kwit) for Smoking Cessation in an Ecological Context: Quantitative Study

BACKGROUND

Mobile health apps can facilitate access to effective treatment and therapeutic information services. However, the real-world effectiveness of mobile apps for smoking cessation and their potential impact in everyday settings remain unclear.

OBJECTIVE

In an ecological context, this study aimed to estimate the engagement rate of a mobile app-based smoking cessation preparation program and its potential impact on users' willingness, ability, and readiness to quit smoking.

METHODS

A total of 2331 "organic users" (ie, users who discover and install a mobile app on their own, without any prompts) chose 1 of 2 program versions of the mobile app (Kwit): the basic version or the premium version. Both versions were identical in design, with 4 more evidence-based content items and strategies in the premium version. Outcomes were analyzed based on automated data registered in the app (engagement rate, motivation to quit, motivation type, motivation levels, and satisfaction level). Mann-Whitney and χ2 tests were used to compare the results of both groups.

RESULTS

As expected, in the ecological context, a high dropout rate was observed at different moments. A significant difference was observed between the 2 versions (n=2331; χ21=5.4; P=.02), with a proportionally higher engagement rate in the premium version (premium=4.7% vs basic=2%). Likewise, differences were also observed between the 2 groups in terms of reasons to quit (n=2331; χ24=19; P≤.001; V=0.08), motivation type (n=2331; χ27=14.7; P=.04), and motivation level. Users of the app's premium version more frequently reported "well-being" (23.3% vs 17.9%) and "planning a pregnancy" (7.4% vs 4.4%) as their primary reasons for quitting smoking compared to those with the basic version. Moreover, they reported being more likely to be driven in the smoking cessation process by intrinsic motivation (premium=28% vs basic=20.4%), as well as feeling significantly more willing (z score=156,055; P≤.001; Cohen d=0.15), able (z score=172,905; P=.04; Cohen d=0.09), and ready (z score=166,390; P=.005; Cohen d=0.12) to stop smoking than users who had the basic version before completion of the preparation program. Among participants who finished each version of the program (premium: 9/189, 4.8%; basic: 47/2142, 2.19%), significant improvements in motivation levels were observed in both groups, although in different areas for each group (willingness levels for the premium group and ability for the basic group).

CONCLUSIONS

These results suggest that even in ecological contexts where engagement rates are meager, the Kwit preparation program can address ambivalence by increasing willingness to change, self-confidence, and readiness to quit among its users, especially those who feel less able to do so. Further development and evaluations are needed to better understand determinants for regular mobile health apps.

Stopping use of E-cigarettes and smoking combustible cigarettes: findings from a large longitudinal digital smoking cessation intervention study in the United States

OBJECTIVE

Digital interventions have been widely implemented to promote tobacco cessation. However, implementations of these interventions have not yet considered how participants' e-cigarette use may influence their quitting outcomes. We explored the association of e-cigarette use and quitting smoking within the context of a study testing a digital tobacco cessation intervention among individuals in the United States who were 18 years and older, smoked combustible cigarettes, and enrolled in the intervention between August 2017 and March 2019.

RESULTS

We identified four e-cigarette user groups (n = 990) based on the participants' baseline and six-month e-cigarette use (non-users, n = 621; recently started users, n = 60; sustained users, n = 187; recently stopped users, n = 122). A multiple logistic regression was used to estimate the adjusted odds ratios (AOR) of six-month quit outcome and the e-cigarette user groups. Compared to e-cigarette non-users, the odds of quitting smoking were significantly higher among recently stopped users (AOR = 1.68, 95% CI [1.06, 2.67], p = 0.03). Participants who were most successful at quitting combustible cigarettes also stopped using e-cigarettes at follow-up, although many sustained using both products. Findings suggest that digital tobacco cessation interventions may carefully consider how to promote e-cigarette use cessation among participants who successfully quit smoking.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT03224520 (July 21, 2017).

Systematic content analysis of self-help smokeless tobacco cessation smartphone applications available in India

Background

The content of smartphone applications (apps) that offer smoking cessation interventions has been appraised in the past. Considering the high prevalence of smokeless tobacco (SLT) use in Southeast Asia, identifying high-quality and credible apps for SLT cessation would be more helpful.

Objective

This study evaluated the technical quality of apps for SLT cessation and their content adherence with the standard tobacco cessation guidelines.

Materials and methods

A systematic search of SLT cessation smartphone apps freely available in the Google PlayStore was conducted using nine relevant search terms, and the first fifty apps under each search term were identified. The technical quality of the apps was rated using the Mobile App Rating Scale (MARS). Adherence of the app content to the standard tobacco cessation guidelines was also determined.

Results

Three apps were found to be relevant for SLT cessation. However, none of the apps was high-quality or incorporated existing evidence on SLT cessation.

Conclusion

Adherence of these apps to the tobacco cessation guidelines by the National Tobacco Control Program (NTCP), India and the National Institute for Health and Care Excellence (NICE), U.K., was limited only to a few checklist parameters.

Technology-based interventions for tobacco smoking prevention and treatment: a 20-year bibliometric analysis (2003-2022)

BACKGROUND

Substance abuse, particularly tobacco smoking, is a significant global public health concern. Efforts have been made to reduce smoking prevalence and promote cessation, but challenges, such as nicotine addiction, marketing tactics by tobacco industry, and cultural acceptability hinder progress. Technology has emerged as a potential tool to address these challenges by providing innovative scalable interventions. The objective of the study was to analyze and map scientific literature on technology-based intervention for tobacco prevention and treatment.

METHODS

A bibliometric methodology was conducted. Scopus database was used to retrieve relevant research articles published between 2003 and 2022. The analysis included publication trends, key contributors, research hotspots, research themes, the most impactful articles, and emerging research topics.

RESULTS

A total of 639 articles were found, with a slow and fluctuating growth pattern observed after 2011. The Journal of Medical Internet Research was the most prominent journal in the field. The United States was the leading country in the field, followed up by the United Kingdom, and the Netherlands. Research hotspots included smoking cessation, randomized controlled trials, and technology-based methods such as internet, mHealth, smartphone apps, text messages, and social media. Four primary research themes were identified: development of smartphone applications, efficacy of text messaging interventions, acceptance and effectiveness of smartphone applications, and interventions targeting young adults and students using mobile phone and social media platforms. The top 10 cited articles demonstrated effectiveness of digital interventions in promoting smoking cessation rates and reducing relapse rates. Emerging research topics included the use of virtual reality interventions, interventions for specific populations through personalized tools, and technology-based interventions in non-Western countries.

CONCLUSIONS

The findings of the current study highlight the potential of technology to address the challenges associated with tobacco smoking. Further future research in this area is warranted to continue advancing the field and developing effective and evidence-based interventions to combat tobacco smoking.

College students' preferences for tobacco treatment: a discrete choice experiment

The purpose of this study was to elicit preferences for the 'format' and 'content' of tobacco treatment among college student smokers, using an online discrete choice experiment (DCE) survey. A DCE survey, supplemented with a think-aloud method, was conducted among 54 college students who smoked combustible cigarettes and/or e-cigarettes. Conditional logistic regression models were constructed to determine optimal profiles of treatment. Cutting down nicotine rather than quitting 'cold turkey' (P < 0.001) and two-way communication (P < 0.001) were viewed as the most critical attributes for the intervention 'format'; changing behaviors rather than social groups/peers (P < 0.001) and autonomy (P < 0.001) were viewed as the most critical attributes for the intervention 'content'. Some preferences varied based on smoking subgroups. Combustible cigarette users preferred interventions with a longer time commitment (P < 0.05) and without nicotine replacement therapies (NRTs) (P < 0.001). Think-aloud data supported the DCE findings and further revealed a strong desire for cutting down nicotine and keeping social groups/peers and misconceptions regarding NRTs. Our study findings can guide tobacco treatment tailored to college students. These treatments should be tailored to specific smoker subgroups.

Baseline characteristics and the factors influencing successful smoking cessation: A comparison between a WeChat smoking cessation mini-program and an offline smoking cessation clinic

INTRODUCTION

Smoking cessation (SC) clinics are a professional SC services in China. However, studies comparing the characteristics and SC rates of smoking populations in SC clinics with those using mobile SC programs are limited. We compared smokers' characteristics, 3-month SC rates, and the factors influencing 3-month SC success, between a large hospital SC clinic and a WeChat SC mini-program.

METHODS

Between January and November 2021, 384 participants voluntarily enrolled in either the hospital SC clinic (Group A: n=243) or the WeChat SC mini-program (Group B: n=141). Both groups underwent a 3-month SC intervention, and their SC status was monitored at 24 hours, 1 week, 1 month, and 3 months after quitting. SC rate was defined as the self-reported rate of continuous SC.

RESULTS

The 3-month SC rate was higher in Group A (42.4%) than in Group B (24.8%). Participants with middle school education had a lower likelihood of SC success than those with primary school or lower (p=0.014). Employees in the enterprise/business/services industries were more likely to have SC success than farmers (p=0.013). Participants with SC difficulty scores of 0-60 were more successful than those with scores >60 (p=0.001, p=0.000, respectively). Participants who quit smoking due to their illness, or other reasons, had a higher likelihood of SC success than those who quit due to concerns about their own and their family's health (p=0.006, p=0.098, respectively). While the likelihood of SC success was lower in those who quit because of the influence of their environment than in those who quit due to concerns about their own and their family's health (p=0.057).

CONCLUSIONS

Both SC clinics and WeChat SC mini-programs achieved satisfactory SC rates. The high accessibility of mobile SC platforms, which save time spent on transportation and medical visits, renders them worth promoting and publicizing as additional SC options for smokers, particularly young smokers.

Developing a Game (Inner Dragon) Within a Leading Smartphone App for Smoking Cessation: Design and Feasibility Evaluation Study

BACKGROUND

Several stand-alone smartphone apps have used serious games to provide an engaging approach to quitting smoking. So far, the uptake of these games has been modest, and the evidence base for their efficacy in promoting smoking cessation is still evolving. The feasibility of integrating a game into a popular smoking cessation app is unclear.

OBJECTIVE

The aim of this paper was to describe the design and iterative development of the Inner Dragon game within Smoke Free, a smartphone app with proven efficacy, and the results of a single-arm feasibility trial as part of a broad program that seeks to assess the effectiveness of the gamified app for smoking cessation.

METHODS

In phase 1, the study team undertook a multistep process to design and develop the game, including web-based focus group discussions with end users (n=15). In phase 2, a single-arm study of Smoke Free users who were trying to quit (n=30) was conducted to assess the feasibility and acceptability of the integrated game and to establish the feasibility of the planned procedures for a randomized pilot trial.

RESULTS

Phase 1 led to the final design of Inner Dragon, informed by principles from psychology and behavioral economics and incorporating several game mechanics designed to increase user engagement and retention. Inner Dragon users maintain an evolving pet dragon that serves as a virtual avatar for the users' progress in quitting. The phase-2 study established the feasibility of the study methods. The mean number of app sessions completed per user was 13.8 (SD 13.1; median 8; range 1-46), with a mean duration per session of 5.8 (median 1.1; range 0-81.1) minutes. Overall, three-fourths (18/24, 75%) of the participants entered the Inner Dragon game at least once and had a mean of 2.4 (SD 2.4) sessions of game use. The use of Inner Dragon was positively associated with the total number of app sessions (correlation 0.57). The mean satisfaction score of participants who provided ratings (11/24, 46%) was 4.2 (SD 0.6) on a 5-point scale; however, satisfaction ratings for Inner Dragon were only completed by 13% (3/24) of the participants.

CONCLUSIONS

Findings supported further development and evaluation of Inner Dragon as a beneficial feature of Smoke Free. The next step of this study is to conduct a randomized pilot trial to determine whether the gamified version of the app increases user engagement over a standard version of the app.

The Effects of Objective Push-Type Sleep Feedback on Habitual Sleep Behavior and Momentary Symptoms in Daily Life: mHealth Intervention Trial Using a Health Care Internet of Things System

BACKGROUND

Sleep is beneficial for physical and mental health. Several mobile and wearable sleep-tracking devices have been developed, and personalized sleep feedback is the most common functionality among these devices. To date, no study has implemented an objective push-type feedback message and investigated the characteristics of habitual sleep behavior and diurnal symptoms when receiving sleep feedback.

OBJECTIVE

We conducted a mobile health intervention trial to examine whether sending objective push-type sleep feedback changes the self-reported mood, physical symptoms, and sleep behavior of Japanese office workers.

METHODS

In total, 31 office workers (mean age 42.3, SD 7.9 years; male-to-female ratio 21:10) participated in a 2-arm intervention trial from November 30 to December 19, 2020. The participants were instructed to indicate their momentary mood and physical symptoms (depressive mood, anxiety, stress, sleepiness, fatigue, and neck and shoulder stiffness) 5 times a day using a smartphone app. In addition, daily work performance was rated once a day after work. They were randomly assigned to either a feedback or control group, wherein they did or did not receive messages about their sleep status on the app every morning, respectively. All participants wore activity monitors on their nondominant wrists, through which objective sleep data were registered on the web on a server. On the basis of the estimated sleep data on the server, personalized sleep feedback messages were generated and sent to the participants in the feedback group using the app. These processes were fully automated.

RESULTS

Using hierarchical statistical models, we examined the differences in the statistical properties of sleep variables (sleep duration and midpoint of sleep) and daily work performance over the trial period. Group differences in the diurnal slopes for mood and physical symptoms were examined using a linear mixed effect model. We found a significant group difference among within-individual residuals at the midpoint of sleep (expected a posteriori for the difference: -15, 95% credible interval -26 to -4 min), suggesting more stable sleep timing in the feedback group. However, there were no significant group differences in daily work performance. We also found significant group differences in the diurnal slopes for sleepiness (P<.001), fatigue (P=.002), and neck and shoulder stiffness (P<.001), which was largely due to better scores in the feedback group at wake-up time relative to those in the control group.

CONCLUSIONS

This is the first mobile health study to demonstrate that objective push-type sleep feedback improves sleep timing of and physical symptoms in healthy office workers. Future research should incorporate specific behavioral instructions intended to improve sleep habits and examine the effectiveness of these instructions.

Exploring Users’ Experiences With a Quick-Response Chatbot Within a Popular Smoking Cessation Smartphone App: Semistructured Interview Study

Background

Engagement with smartphone apps for smoking cessation tends to be low. Chatbots (ie, software that enables conversations with users) offer a promising means of increasing engagement.

Objective

We aimed to explore smokers’ experiences with a quick-response chatbot (Quit Coach) implemented within a popular smoking cessation app and identify factors that influence users’ engagement with Quit Coach.

Methods

In-depth, one-to-one, semistructured qualitative interviews were conducted with adult, past-year smokers who had voluntarily used Quit Coach in a recent smoking cessation attempt (5/14, 36%) and current smokers who agreed to download and use Quit Coach for a minimum of 2 weeks to support a new cessation attempt (9/14, 64%). Verbal reports were audio recorded, transcribed verbatim, and analyzed within a constructivist theoretical framework using inductive thematic analysis.

Results

A total of 3 high-order themes were generated to capture users’ experiences and engagement with Quit Coach: anthropomorphism of and accountability to Quit Coach (ie, users ascribing human-like characteristics and thoughts to the chatbot, which helped foster a sense of accountability to it), Quit Coach’s interaction style and format (eg, positive and motivational tone of voice and quick and easy-to-complete check-ins), and users’ perceived need for support (ie, chatbot engagement was motivated by seeking distraction from cravings or support to maintain motivation to stay quit).

Conclusions

Anthropomorphism of a quick-response chatbot implemented within a popular smoking cessation app appeared to be enabled by its interaction style and format and users’ perceived need for support, which may have given rise to feelings of accountability and increased engagement.

Motivators of impulsivity to smoke waterpipe tobacco among Nigerian youth who smoke waterpipe tobacco: the moderating role of social media normalisation of waterpipe tobacco

BACKGROUND

Impulsivity is a formidable cause of waterpipe tobacco smoking among youth, however, it is understudied among African youth. Using PRIME behavioural theory, this study aimed to develop a model that examines the motivators of impulsivity to smoke waterpipe tobacco in linkage to the moderating role of social media normalisation of waterpipe tobacco, specifically among youth in Nigeria who smoke waterpipe tobacco.

METHODS

Data were drawn from 695 respondents who smoke waterpipe tobacco across six Nigerian universities in the South-West zone using the chain-referral sampling procedure. Descriptive analyses of the obtained data were carried out using the Statistical Package for Social Sciences (SPSS) version 25. The constructs in the developed model were validated through Partial Least Squares Structural Equation Modelling (PLS-SEM) in SmartPLS version 3.

RESULTS

Among Nigerian youth who smoke waterpipe tobacco, intention (β = 0.442, P < 0.001) was the strongest motivator of impulsivity to smoke waterpipe tobacco as compared to positive evaluations (β = 0.302, P < 0.001). In addition, social media normalisation of waterpipe tobacco acted as a moderator that strengthened the relationship between intention and impulsivity (β = 0.287, P < 0.01), as well as, between positive evaluations and impulsivity (β = 0.186, P < 0.01) among youth.

CONCLUSION

Intention greatly instigates Nigerian youth's impulsivity to smoke waterpipe tobacco, and social media normalisation of waterpipe tobacco also considerably increases their impulsivity to smoke waterpipe tobacco. Youth-focused educational waterpipe tobacco cessation-oriented programmes that utilise diverse constructive-based learning approaches like illustrative learning and counselling, can help to enlighten and encourage Nigerian youth on the importance of shunning the desirability to smoke waterpipe tobacco.

Applying Collective Intelligence in Health Recommender Systems for Smoking Cessation: A Comparison Trial

Background: Health recommender systems (HRSs) are intelligent systems that can be used to tailor digital health interventions. We compared two HRSs to assess their impact providing smoking cessation support messages. Methods: Smokers who downloaded a mobile app to support smoking abstinence were randomly assigned to two interventions. They received personalized, ratable motivational messages on the app. The first intervention had a knowledge-based HRS (n = 181): it selected random messages from a subset matching the users’ demographics and smoking habits. The second intervention had a hybrid HRS using collective intelligence (n = 190): it selected messages applying the knowledge-based filter first, and then chose the ones with higher ratings provided by other similar users in the system. Both interventions were compared on: (a) message appreciation, (b) engagement with the system, and (c) one’s own self-reported smoking cessation status, as indicated by the last seven-day point prevalence report in different time intervals during a period of six months. Results: Both interventions had similar message appreciation, number of rated messages, and abstinence results. The knowledge-based HRS achieved a significantly higher number of active days, number of abstinence reports, and better abstinence results. The hybrid algorithm led to more quitting attempts in participants who completed their user profiles.

Mobile phone and internet use among people who inject drugs: Implications for mobile health interventions

Background: Mobile health (mHealth) interventions have the potential to improve substance use treatment engagement and outcomes, and to reduce risk behaviors among people who inject drugs (PWID). However, there are few studies assessing mobile technology use among PWID and none have investigated continuity of mobile phone use. Methods: We surveyed 494 PWID. We used bivariate (independent-sample t- and chi-square tests) and multivariate (logistic regression) analyses to determine whether mobile phone and/or internet use differed as a function of participant- and/or injection-related characteristics. Results: Most participants (77%) had a mobile phone, with 67% having a phone that was free of charge. Participants with a phone were significantly less likely to be homeless (AOR = 0.28), to have shared syringes (AOR = 0.53), and to have reused syringes (AOR = 0.26) in the past 3 months. We observed high rates of phone and number turnover, with more than half reporting that they got a new phone (57%) and/or number (56%) at least once within the past 3 months. Most participants were familiar with using the internet (80% ever use), though participants who had ever used the internet were younger (AOR = 0.89), were less likely to be homeless (AOR = 0.38), were less likely to have shared syringes (AOR = 0.49), and were more likely to have injected methamphetamine by itself (AOR = 2.49) in the past 3 months. Conclusions: Overall, mobile technology and internet use was high among our sample of PWID. Several factors should be considered in recruiting diverse samples of PWID to minimize bias in mHealth study outcomes, including mobile phone access and protocol type (text- vs internet-based).

Feasibility of a Smoking Cessation Smartphone App (Quit with US) for Young Adult Smokers: A Single Arm, Pre-Post Study

While smartphone applications (apps) have been shown to enhance success with smoking cessation, no study has been conducted among young adult smokers aged 18-24 years in Thailand. Quit with US was developed based on the 5 A's model and self-efficacy theory. This single arm, pre-post study was conducted aiming to assess results after using Quit with US for 4 weeks. The primary outcome was a biochemically verified 7-day point prevalence of smoking abstinence. The secondary outcomes included smoking behaviors, knowledge and attitudes toward smoking and smoking cessation, and satisfaction and confidence in the smartphone app. A total number of 19 young adult smokers were included; most participants were males (68.4%) with the mean (SD) age of 20.42 (1.46) years. After 4 weeks of study, the primary outcome demonstrated a smoking cessation rate of 31.6%. All 19 participants expressed better smoking behaviors and better knowledge and attitudes toward smoking and smoking cessation. Further, they were satisfied with the smartphone app design and content and expressed confidence in using it. These findings provided preliminary evidence that Quit with US was found to be a potentially effective smoking cessation smartphone app for young adult smokers.

What do people want in a smoking cessation app? An analysis of user reviews and app quality

INTRODUCTION

Mobile smoking cessation (mCessation) apps have the potential to complement and enhance existing interventions, but many are of low quality. Exploring app reviews can provide a broader understanding of user experiences and engagement, to enhance the quality, acceptability and effectiveness of future developments.

METHODS

Publicly available user reviews and ratings of smoking cessation apps were mined from Google Play TM and the App Store ® via a targeted two-stage search strategy. English language smoking cessation apps with at least 20 consumer reviews between 2011 and 2020 were included. User reviews were thematically analysed using Braun & Clarke's framework. Apps were independently scored using the Mobile Apps Rating Scale (MARS) and compared to average user star ratings.

RESULTS

Forty-eight versions of 42 apps, encompassing 1,414 associated reviews, met eligibility criteria. Inductive coding of reviews produced 1,084 coding references including reviews coded across multiple nodes. Themes generated included: (1) supportive characteristics/tools; (2) useability; (3) influence on smoking behaviour; (4) benefits of quitting; and (5) role as a supplementary tool for quitting. The mean MARS score of 36 free and accessible apps was 3.10 (SD 0.71) with mean scores ranging from 2.00 to 4.47. An inverse relationship between MARS scores and average user star ratings was observed .

CONCLUSIONS

App personalisation, relationality, functionality and credibility were important to users, and should be considered as key design components for future apps. Differences between user star ratings and MARS scores may illustrate competing priorities of consumers and researchers, and the importance of a co-design development method.

IMPLICATIONS

This is the first study to use unsolicited user reviews from a large population to understand the general mCessation user experience in relation to making a quit attempt. Our findings highlight specific features favoured and disliked by users, including their influence on engagement, and supports previous findings that mCessation applications need to be highly tailorable, functional, credible and supportive. We recommend a consumer-driven, co-design approach for future mCessation app developments to optimise user acceptability and engagement.

Examination of the relationship between lapses and weight loss in a smartphone-based just-in time adaptive intervention

We developed a smartphone-based just-in-time adaptive intervention (JITAI), called OnTrack, that provides personalized intervention to prevent dietary lapses (i.e., nonadherence from the behavioral weight loss intervention diet). OnTrack utilizes ecological momentary assessment (EMA; repeated electronic surveys) for self-reporting lapse triggers, predicts lapses using machine learning, and provides brief intervention to prevent lapse. We have established preliminary feasibility, acceptability, and efficacy of OnTrack, but no study has examined our hypothesized mechanism of action: reduced lapse frequency will be associated with greater weight loss while using OnTrack. This secondary analysis investigated the association between lapse frequency and the weekly percentage of weight loss. Post hoc analyses evaluated the moderating effect of OnTrack engagement on this association. Participants (N = 121) with overweight/obesity (MBMI = 34.51; 84.3% female; 69.4% White) used OnTrack with a digital weight loss program for 10 weeks. Engagement with OnTrack (i.e., EMA completed and interventions accessed) was recorded automatically, participants self-reported dietary lapses via EMA, and weighed weekly using Bluetooth scales. Linear mixed models with a random effect of subject and fixed effect of time revealed a nonsignificant association between weekly lapses and the percentage of weight loss. Post hoc analyses revealed a statistically significant moderation effect of OnTrack engagement such that fewer EMA and interventions completed conferred the expected associations between lapses and weight loss. Lapses were not associated with weight loss in this study and one explanation may be the influence of engagement levels on this relationship. Future research should investigate the role of engagement in evaluating JITAIs.

Effect of a mobile just-in-time implementation intention intervention on momentary smoking lapses in smoking cessation attempts among Asian American young adults

Identifying vulnerable windows for a given problematic behavior and providing timely and appropriate support are critical for building an effective just-in-time (JIT) intervention for behavioral change. We developed and evaluated an implementation intention (II) based, JIT cessation intervention prototype to support Asian American young adult smokers to prevent lapses in their cessation attempts in real-time. We examined how a JIT II reminder may prevent lapses during self-identified high-risk smoking situation (HRSS) as a microtemporal process. We also tested whether the effect of JIT reminder changes over the course of study and differed between those who used their own versus project loan phones. Asian American young adult smokers (N = 57) who were interested in quitting or reducing smoking participated in a 4 week, mobile-based, cessation study (MyQuit USC, MQU). MQU is a JIT mobile app that deploys a user-specified II reminder at user-specified HRSS and assesses momentary lapse status. Generalized mixed linear models were conducted to assess the effect of the JIT intervention on lapse prevention. We found a significant interaction effect (p = .03) such that receiving JIT reminder reduced the likelihood of lapses for participants using their own phones but not for the loaners. The results also showed that when participants enacted the suggested II, they were less likely to lapse (p < .001). The JIT effect did not change over time in study (p = .21). This study provides evidence that receiving a reminder of a smoker's own plan just before a self-identified risky situation on a familiar device and successfully executing specified plans can be helpful in preventing lapses. Our results highlighted factors to consider when designing and refining a JIT intervention.

Supportive Accountability and Mobile App Use in a Tobacco Control Intervention Targeting Low-Income Minority Mothers Who Smoke: Observational Study

BACKGROUND

Smartphone mobile apps are frequently used in standalone or multimodal smoking cessation interventions. However, factors that impede or improve app usage are poorly understood.

OBJECTIVE

This study used the supportive accountability model to investigate factors that influence app usage in the context of a trial designed to reduce maternal smoking in low-income and predominantly minority communities.

METHODS

We conducted a secondary analysis of data (N=181) from a randomized controlled trial that included a smoking cessation app (QuitPal-m). Supportive accountability was measured by the number of times a participant was advised by their cessation counselor to use QuitPal-m. Participants reported app use helpfulness and barriers. Investigators tracked reported phone and technical problems that impeded app use.

RESULTS

Most participants rated the app as very helpful (103/155, 66.5%), but daily use declined rapidly over time. App use was positively related to the level of perceived app helpfulness (P=.02) and education (P=.002) and inversely related to perceived barriers (P=.003), phone technical problems (P<.001), and cigarettes smoked per day at the end of treatment (P<.001). Participants used the app a greater proportion of the days following app advice than those preceding app advice (0.45 versus 0.34; P<.001). The positive relation between counselor app advice and app usage 24 hours after receiving advice was stronger among smokers with no plan to quit than in those planning to quit (P=.03), independent of education and phone or app problems.

CONCLUSIONS

Findings show the utility of supportive accountability for increasing smoking cessation app use in a predominantly low-income, minority population, particularly if quit motivation is low. Results also highlight the importance of addressing personal and phone/technical barriers in addition to adding supportive accountability.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02602288; https://clinicaltrials.gov/ct2/show/NCT02602288.

Are Machine Learning Methods the Future for Smoking Cessation Apps?

Smoking cessation apps provide efficient, low-cost and accessible support to smokers who are trying to quit smoking. This article focuses on how up-to-date machine learning algorithms, combined with the improvement of mobile phone technology, can enhance our understanding of smoking behaviour and support the development of advanced smoking cessation apps. In particular, we focus on the pros and cons of existing approaches that have been used in the design of smoking cessation apps to date, highlighting the need to improve the performance of these apps by minimizing reliance on self-reporting of environmental conditions (e.g., location), craving status and/or smoking events as a method of data collection. Lastly, we propose that making use of more advanced machine learning methods while enabling the processing of information about the user’s circumstances in real time is likely to result in dramatic improvement in our understanding of smoking behaviour, while also increasing the effectiveness and ease-of-use of smoking cessation apps, by enabling the provision of timely, targeted and personalised intervention.

Behavior Change Techniques in Popular Mobile Apps for Smoking Cessation in France: Content Analysis

Background

The mobile app market differs from country to country, and to date, no previous review of the content quality of smoking cessation apps has been conducted in France.

Objective

This study aimed to examine the general quality of the most popular smoking cessation apps in France and also determine the degree to which apps adhere to established behavioral and cognitive techniques (BCTs) proven effective in clinical practice.

Methods

A systematic research of smoking cessation apps was conducted in both the Google Play Store and Apple Store in the French market. The general quality of popular apps was rated with the Mobile App Rating Scale (MARS), and the therapeutic quality was assessed with the ratio of adherence of the behavior change technique taxonomy for smoking cessation treatment.

Results

A total of 14 mobile apps met all the inclusion criteria of the content analysis. The interrater reliability varied from “substantial” (0.79) to “almost perfect” (0.9) for the two measures. The mean MARS score was 3.5 out of 5 (median 3.6, IQR 0.6 [3.2-3.8]). The findings suggest that popular apps focus primarily on the functionality dimension of the MARS scale (4.2/5). The mean number of BCTs was 22, with a large difference between apps (minimum 4, maximum 38). At least half of the apps addressed motivation (8.8/14, 63%) and advised on using behavioral skills in order to quit smoking or stay a nonsmoker (8.7/14, 62%). However, only a handful of apps gathered important information (5.9/14, 42%) in order to deliver proper advice regarding the use of approved medication or the implementation of behavioral techniques (4.3/14, 31%). The mean MARS score was positively correlated with the price (r=0.70, P=.007) and the number of BCTs used (r=0.67, P=.01). User rating was not correlated with any quality scale (P=.67).

Conclusions

The content quality of popular smoking cessation apps in France varied by app type and price. Most popular apps propose in general good quality content but lack implementation of evidence-based BCTs associated with effectiveness on smoking cessation treatment. Further research is needed to evaluate the improvement in the content quality of smoking cessation apps in France.

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

Background

Decreasing 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.

Objective

This 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.

Methods

Smokers 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.

Results

A 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.

Conclusions

The 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.

Durability of Abstinence After Completing a Comprehensive Digital Smoking Cessation Program Incorporating a Mobile App, Breath Sensor, and Coaching: Cohort Study

BACKGROUND

Despite decreasing prevalence over the last several decades, cigarette smoking remains the leading cause of preventable death and disease, underscoring the need for innovative, effective solutions. Pivot is a novel, inclusive smoking cessation program designed for smokers along the entire spectrum of readiness to quit. Pivot leverages proven methods and technological advancements, including a personal portable breath carbon monoxide sensor, smartphone app, and in-app text-based coaching. We previously reported outcomes from the end of active Pivot program participation in 319 adult smokers. Herein, we report longer-term follow up in this cohort.

OBJECTIVE

The aim of this study was to assess and report participant outcomes 3 months after completion of Pivot, including smoking behavior, quit rates, continuous abstinence rates and durability, and predictors of abstinence.

METHODS

This prospective remote cohort study included US-based cigarette smokers aged 18 to 65 years who smoked ≥5 cigarettes per day (CPD). Three months after completion of active participation in Pivot, final follow-up data were collected via an online questionnaire. Outcomes included smoking behavior (CPD and quit attempts), self-reported quit rates (7- and 30-day point prevalence abstinence [PPA]), and continuous abstinence rates (proportion who achieved uninterrupted abstinence) and duration. Exploratory regression analyses were performed to identify baseline characteristics associated with achievement of 7-day PPA, 30-day PPA, and continuous abstinence.

RESULTS

A total of 319 participants completed onboarding (intention-to-treat [ITT]); 288/319 participants (90.3%) completed follow up (completers) at a mean of 7.2 (SD 1.2) months after onboarding. At final follow up, CPD were reduced by 52.6% (SE 2.1; P<.001) among all 319 participants, and most completers (152/288, 52.8%) reduced their CPD by at least 50%. Overall, most completers (232/288, 80.6%) made at least one quit attempt. Quit rates increased after the end of Pivot; using ITT analyses, 35.4% (113/319) achieved 7-day PPA and 31.3% (100/319) achieved 30-day PPA at final follow up compared with 32.0% (102/319) and 27.6% (88/319), respectively, at the end of the Pivot program. Continuous abstinence was achieved in about a quarter of those who onboarded (76/319, 23.8%) and in most who reported 30-day PPA at the end of Pivot (76/88, 86.4%), with a mean abstinence duration of 5.8 (SD 0.6) months. In exploratory regression analyses, lower baseline CPD, more positive baseline attitudes reflecting higher self-efficacy (higher confidence to quit and lower perceived difficulty of quitting), and higher education were associated with achieving abstinence.

CONCLUSIONS

This study provides the first longer-term outcomes of the Pivot smoking cessation program. At final follow up, quit rates increased and continuous abstinence was favorable; the majority who achieved abstinence at the end of Pivot sustained abstinence throughout follow up. Decreases in CPD persisted and most participants made a quit attempt. Overall, final follow-up outcomes were stable or improved when compared to previous outcomes from the end of the program. These findings validate earlier results, and suggest that Pivot is an effective and durable solution for smoking cessation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03295643; https://clinicaltrials.gov/ct2/show/NCT03295643.

Does addition of craving management tools in a stop smoking app improve quit rates among adult smokers? Results from BupaQuit pragmatic pilot randomised controlled trial

OBJECTIVES

Delivery of craving management tools via smartphone applications (apps) may improve smoking cessation rates, but research on such programmes remains limited, especially in real-world settings. This study evaluated the effectiveness of adding craving management tools in a cessation app (BupaQuit).

METHODS

The study was a two-arm pragmatic pilot parallel randomised controlled trial, comparing a fully-automated BupaQuit app with craving management tool with a control app version without craving management tool. A total of 425 adult UK-based daily smokers were enrolled through open online recruitment (February 2015-March 2016), with no researcher involvement, and individually randomised within the app to the intervention (n = 208) or control (n = 217). The primary outcome was self-reported 14-day continuous abstinence assessed at 4-week follow-up. Secondary outcomes included 6-month point-prevalence and sustained abstinence, and app usage. The primary outcome was assessed with Fisher's exact test using intent to treat with those lost to follow-up counted as smoking. Participants were not reimbursed.

RESULTS

Re-contact rates were 50.4% at 4 weeks and 40.2% at 6 months. There was no significant difference between intervention and control arms on the primary outcome (13.5% vs 15.7%; p = 0.58; relative risk = 0.86, 95% confidence interval = 0.54-1.36) or secondary cessation outcomes (6-month point prevalence: 14.4% vs 17.1%, p = 0.51; relative risk = 0.85, 95% confidence interval = 0.54-1.32; 6-month sustained: 11.1% vs 13.4%, p = 0.55; relative risk = 0.83, 95% confidence interval = 0.50-1.38). Bayes factors supported the null hypothesis (B[0, 0, 1.0986] = 0.20). Usage was similar across the conditions (mean/median logins: 9.6/4 vs 10.5/5; time spent: 401.8/202 s vs 325.8/209 s).

CONCLUSIONS

The addition of craving management tools did not affect cessation, and the limited engagement with the app may have contributed to this.

Smartphone health apps for tobacco Cessation: A systematic review

BACKGROUND

Given the low retention and lack of persistent support by traditional tobacco cessation programs, evidence-based smartphone app-supported interventions can be an important tobacco control component. The objective of this systematic review was to identify and evaluate the types of studies that use smartphone apps for interventions in tobacco cessation.

METHODS

We conducted a systematic review of PubMed (1946-2019), EMBASE (1974-2019), and PsycINFO (1806-2019) databases with keywords related to smartphone-supported tobacco cessation. Included articles were required to meet 3 baseline screening criteria: 1) be written in English, 2) include an abstract, and 3) be a full, peer-reviewed manuscript. The criteria for the second level of review were: 1) primary outcome of tobacco cessation, 2) intervention study, and 3) smartphone app as primary focus of study.

RESULTS

Of 1973 eligible manuscripts, 18 met inclusion criteria. Most studies (n = 17) recruited adult participants (18 + years); one included teens (16 + years). Tobacco cessation was usually self-reported (n = 11), compared to biochemical verification (n = 3) or both (n = 4). There were 11 randomized controlled trials, 4 of which reported statistically significant results, and 7 single-arm trials that reported a mean abstinence rate of 33.9%.

DISCUSSION

The majority of studies that use tobacco cessation apps as an intervention delivery modality are mostly at the pilot/feasibility stage. The growing field has resulted in studies that varied in methodologies, study design, and inclusion criteria. More consistency in intervention components and larger randomized controlled trials are needed for tobacco cessation smartphone apps.

Effects of a Mobile App Called Quittr, Which Utilizes Premium Currency and Games Features, on Improving Engagement With Smoking Cessation Intervention: Pilot Randomized Controlled Trial

BACKGROUND

Numerous mobile health (mHealth) apps have been developed to support smokers attempting to quit smoking. Although these apps have been reported to be successful, only modest improvements in the quit rate have been measured. It has been proposed that efforts to improve user engagement and retention may improve the quit rate further. Owing to the high cost of smoking-related disease, it is considered worthwhile to pursue even small improvements.

OBJECTIVE

The aim of this study was to test a novel smartphone app that leverages premium currency strategies developed by the mobile games industry in an attempt to improve engagement and retention with a smoking cessation intervention.

METHODS

We designed and developed a smoking cessation app called "Quittr" in line with previously developed smoking cessation mHealth apps. In addition to this established framework, we added a stand-alone fully featured city-building clicker-style game called "Tappy Town," and a premium virtual currency called "QuitCoins." The user earns QuitCoins for using the app in a way that contributes positively toward their quit attempt, and they can redeem these coins in Tappy Town for bonuses. To establish whether these features improved engagement and retention, we ran a 5-month randomized controlled trial where the intervention group had the full app with the extra games features, while the control group had the standard app only. Recruitment was performed via web-based advertising. Participants (N=175) had no direct contact with the researchers or other support staff.

RESULTS

No significant differences in terms of engagement, retention, or smoking outcomes were found between the control and intervention groups. However, survey data indicated that the majority of the participants valued Tappy Town (10/17, 59%) and the QuitCoins rewards system (13/17, 77%). Usage data also suggested that Tappy Town was widely played and was generally appealing to users (mean total time spent in app, control group: 797 seconds vs intervention group: 3502 seconds, P<.001). Analysis of the results suggests that users in the intervention group may have been negatively affected by the aspects of the chosen design, and some theories were explored to explain this unexpected outcome.

CONCLUSIONS

Although the novel features of the Quittr app failed to improve the key outcomes measured in this study, there were enough positive indications to warrant further exploration of the concept. Additional research will be required to identify and correct any design flaws that may have adversely affected our participants before a follow-up study can be completed.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Register ACTRN12617000491369; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372661&isReview=true.

Craving to Quit: A Randomized Controlled Trial of Smartphone App-Based Mindfulness Training for Smoking Cessation

INTRODUCTION

Mindfulness training may reduce smoking rates and lessen the association between craving and smoking. This trial tested the efficacy of mindfulness training via smartphone app to reduce smoking. Experience sampling (ES) was used to measure real-time craving, smoking, and mindfulness.

METHODS

A researcher-blind, parallel randomized controlled trial compared the efficacy of mobile mindfulness training with experience sampling (MMT-ES; Craving to Quit) versus experience sampling only (ES) to (1) increase 1-week point-prevalence abstinence rates at 6 months, and (2) lessen the association between craving and smoking. A modified intent-to-treat approach was used for treatment starters (MMT-ES n = 143; ES n = 182; 72% female, 81% white, age 41 ± 12 year).

RESULTS

No group difference was found in smoking abstinence at 6 months (overall, 11.1%; MMT-ES, 9.8%; ES, 12.1%; χ2(1) = 0.43, p = .51). From baseline to 6 months, both groups showed a reduction in cigarettes per day (p < .0001), craving strength (p < .0001) and frequency (p < .0001), and an increase in mindfulness (p < .05). Using ES data, a craving by group interaction was observed (F(1,3785) = 3.71, p = .05) driven by a stronger positive association between craving and cigarettes per day for ES (t = 4.96, p < .0001) versus MMT-ES (t = 2.03, p = .04). Within MMT-ES, the relationship between craving and cigarettes per day decreased as treatment completion increased (F(1,104) = 4.44, p = .04).

CONCLUSIONS

Although mindfulness training via smartphone app did not lead to reduced smoking rates compared with control, our findings provide preliminary evidence that mindfulness training via smartphone app may help lessen the association between craving and smoking, an effect that may be meaningful to support quitting in the longer term.

IMPLICATIONS

This is the first reported full-scale randomized controlled trial of any smartphone app for smoking cessation. Findings provide preliminary evidence that smartphone app-based MMT-ES may lessen the association between craving and smoking.

TRIAL REGISTRATION

Clinicaltrials.gov NCT02134509.

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

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.

Potentials and pitfalls of increasing prosocial behavior and self-efficacy over time using an online personalized platform

Background

This longitudinal mixed methods experimental study aimed to better understand the interplay between digital technology exposure over time, self-efficacy, and prosocial behavior in everyday contexts.

Methods

66 psychology students tracked their daily prosocial behavior over three weeks. Additionally, half of the participants were randomly assigned to receive access to an online platform, which made personalized suggestions for prosocial actions to complete. Qualitative post-study interviews complemented quantitative measures.

Results

Platform exposure had no measurable impact beyond that of tracking over time on either prosocial behavior or self-efficacy. Tracking increased self-efficacy to perform everyday prosocial actions, but did not affect self-efficacy to impact change. Prosocial behavior was predicted by self-efficacy to impact change. Enjoyment of the platform predicted completing higher numbers of suggested prosocial actions and was related to a higher likelihood to continue using the platform in the future. Avenues for increasing platform effectiveness include context-specific action personalization, an effective reminder system, and better support for the development of self-efficacy to impact change through meaningful actions.

Conclusion

Technology for prosocial behavior should be enjoyable, capable of being seamlessly integrated into everyday life, and ensure that suggested actions are perceived as meaningful in order to support the sustainable development of self-efficacy and prosocial behavior over time.

A Mobile Health Solution Complementing Psychopharmacology-Supported Smoking Cessation: Randomized Controlled Trial

Background

Smoking cessation is a persistent leading public health challenge. Mobile health (mHealth) solutions are emerging to improve smoking cessation treatments. Previous approaches have proposed supporting cessation with tailored motivational messages. Some managed to provide short-term improvements in smoking cessation. Yet, these approaches were either static in terms of personalization or human-based nonscalable solutions. Additionally, long-term effects were neither presented nor assessed in combination with existing psychopharmacological therapies.

Objective

This study aimed to analyze the long-term efficacy of a mobile app supporting psychopharmacological therapy for smoking cessation and complementarily assess the involved innovative technology.

Methods

A 12-month, randomized, open-label, parallel-group trial comparing smoking cessation rates was performed at Virgen del Rocío University Hospital in Seville (Spain). Smokers were randomly allocated to a control group (CG) receiving usual care (psychopharmacological treatment, n=120) or an intervention group (IG) receiving psychopharmacological treatment and using a mobile app providing artificial intelligence–generated and tailored smoking cessation support messages (n=120). The secondary objectives were to analyze health-related quality of life and monitor healthy lifestyle and physical exercise habits. Safety was assessed according to the presence of adverse events related to the pharmacological therapy. Per-protocol and intention-to-treat analyses were performed. Incomplete data and multinomial regression analyses were performed to assess the variables influencing participant cessation probability. The technical solution was assessed according to the precision of the tailored motivational smoking cessation messages and user engagement. Cessation and no cessation subgroups were compared using t tests. A voluntary satisfaction questionnaire was administered at the end of the intervention to all participants who completed the trial.

Results

In the IG, abstinence was 2.75 times higher (adjusted OR 3.45, P=.01) in the per-protocol analysis and 2.15 times higher (adjusted OR 3.13, P=.002) in the intention-to-treat analysis. Lost data analysis and multinomial logistic models showed different patterns in participants who dropped out. Regarding safety, 14 of 120 (11.7%) IG participants and 13 of 120 (10.8%) CG participants had 19 and 23 adverse events, respectively (P=.84). None of the clinical secondary objective measures showed relevant differences between the groups. The system was able to learn and tailor messages for improved effectiveness in supporting smoking cessation but was unable to reduce the time between a message being sent and opened. In either case, there was no relevant difference between the cessation and no cessation subgroups. However, a significant difference was found in system engagement at 6 months (P=.04) but not in all subsequent months. High system appreciation was reported at the end of the study.

Conclusions

The proposed mHealth solution complementing psychopharmacological therapy showed greater efficacy for achieving 1-year tobacco abstinence as compared with psychopharmacological therapy alone. It provides a basis for artificial intelligence–based future approaches.

Trial Registration

ClinicalTrials.gov NCT03553173; https://clinicaltrials.gov/ct2/show/NCT03553173

International Registered Report Identifier (IRRID)

RR2-10.2196/12464

A randomized controlled trial of a smoking cessation smartphone application with a carbon monoxide checker

Evidence of the long-term efficacy of digital therapies for smoking cessation that include a smartphone application (app) is limited. In this multi-center randomized controlled trial, we tested the efficacy of a novel digital therapy for smoking cessation: the "CureApp Smoking Cessation (CASC)" system, including a CASC smartphone app, a web-based patient management PC software for primary physicians, and a mobile exhaled carbon monoxide (CO) checker. A total of 584 participants with nicotine dependence were recruited from October 2017 to January 2018, and allocated 1:1 to the CASC intervention group or the control group. Both groups received a standard smoking cessation treatment with pharmacotherapy and counseling for 12 weeks. Meanwhile, the intervention group used the CASC system, and the control group used a control-app without a mobile CO checker, each for 24 weeks. The primary outcome was the biochemically validated continuous abstinence rate (CAR) from weeks 9 to 24. The main secondary outcome was an extended CAR from weeks 9 to 52. Except for 12 participants who did not download or use the apps, 285 participants were assigned to the intervention group, and 287, to the control. CAR from weeks 9 to 24 in the intervention group was significantly higher than that in the control group (63.9% vs. 50.5%; odds ratio [OR], 1.73; 95% confidence interval [CI], 1.24 to 2.42; P = 0.001). The CAR from weeks 9 to 52 was also higher in the intervention group than that in the control group (52.3% vs. 41.5%; OR, 1.55; 95% CI, 1.11 to 2.16; P = 0.010). No specific adverse events caused by the CASC system were reported. Augmenting standard face-to-face counseling and pharmacotherapy with a novel smartphone app, the CASC system significantly improved long-term CARs compared to standard treatment and a minimally supportive control app.

Evidence-based policy making for health promotion to reduce the burden of non-communicable diseases in Moldova

The Republic of Moldova faces several concurrent health challenges most notably an increase in chronic non-communicable diseases, spiralling health care costs and widening health inequalities. To accelerate progress in their resolution there is a need for new and innovative health promotion and behaviour change communication interventions. The Ministry of Health, Labour and Social Protection in collaboration with the newly created National Agency for Public Health held a conference on the occasion of the Moldovan National Day of Health Promotion on 14th March 2018 in which national and invited international experts exchanged their views on (1) best practice examples of behaviour change interventions, health promotion activities and lessons learned from the UK and elsewhere; and (2) possible ways forward for Moldova to implement cost-effective and evidence-based intersectoral health promotion programmes. The experts provided recommendations on implementing behaviour change interventions to reduce and prevent obesity; on the creation of a favourable tobacco control environment to reduce smoking prevalence; and on how physical activity programme design can benefit from health psychology research. All these strategies could foster health promotion activities and ultimately contribute to improving the health outcomes of the Moldovan population.

The Psychological Models of Health-related Behavior in Understanding Sugars Intake in Adults: A Review

Free sugars intake plays a major role in dental caries formation and other general health issues such as obesity. Therefore, interventions, which assist individuals or populations in the control of their free sugars intake, are of central importance in caries prevention strategies. There is good evidence that behavioral interventions benefit from a foundation in conceptual theories of behavior change founded on empirical data. In this review, we discuss the future application of seven theories, including six common psychological theories in predicting and developing interventions to reduce free sugars intake related to dental caries among adults. For each model, we summarize its key features and the data derived from its application in general and oral health settings and make recommendations for future research. We searched Medline, PsycINFO, Global Health, PubMed, and Embase databases to identify items dealing with dental caries, adults, sugars intake, and six psychological theories. These included the Transtheoretical Model of Change, Theory of Planned Behavior, Social Cognitive Theory, Information-Motivation-Behavioral Skills model, PRIME Theory, and Behavior Change Wheel theories. We searched literature published in the last 10 years, and priority was given to systematic reviews and randomized control trials. Although there is extensive literature on the application of the six psychological theories, there is a gap in knowledge about their effectiveness in reducing free sugars intake related to dental caries among adults. There is a need for better-designed trials of interventions based on the clear operationalization of psychological constructs to reduce sugars intake among the adult population.

Trends in and factors associated with the adoption of digital aids for smoking cessation and alcohol reduction: A population survey in England

BACKGROUND

Digital smoking cessation and alcohol reduction aids are widely available in England. To estimate their public health impact, researchers need to consider their adoption in the target population. We assessed adoption rates, and characteristics of adopters, of digital smoking cessation and alcohol reduction aids in England.

METHODS

3655 smokers and 2998 high-risk drinkers (defined as a score of >4 on the Alcohol Use Disorders Identification Test-Consumption; AUDIT-C) who had made a past-year quit/reduction attempt were surveyed as part of the Smoking and Alcohol Toolkit Studies between January 2015-October 2018. Respondents provided information on socio-demographic characteristics and whether they had used a digital aid in a recent quit/reduction attempt.

RESULTS

2.7 % (95 % CI 2.2%-3.0%) of smokers and 3.6 % (95 % CI 2.9%-4.0%) of drinkers who had made a past-year quit/reduction attempt (26.9 % and 15.3 %, respectively) had used a digital aid. Survey year was not significantly associated with use in smokers or drinkers. None of the baseline characteristics were significantly associated with the use of a digital aid in smokers. Drinkers with high motivation to reduce alcohol consumption (ORadj = 2.49, 95 % CI 1.63-3.77, p <  .001) and higher AUDIT scores (ORadj = 1.07, 95 % CI 1.03-1.11, p < .001) had greater odds of adoption.

CONCLUSIONS

Digital smoking cessation and alcohol reduction aids are rarely used by smokers or high-risk drinkers attempting to quit/cut down in England, indicating that most of the target population is not being reached. Despite overall digital access improving, adoption rates remained similarly low between 2015-2018.

A Behavioral Activation Mobile Health App for Smokers With Depression: Development and Pilot Evaluation in a Single-Arm Trial

Background

The integration of Behavioral Activation Treatment for Depression (BAT-D) into smoking cessation interventions is a promising approach to address depression as a barrier to quitting. However, this approach has only been tested as a face-to-face intervention, which has low reach.

Objective

The aims of the study were to develop a BAT-D mobile health app with high potential reach and determine its feasibility, acceptability, and preliminary effects on theory-based behavioral processes of behavioral activation, reduced depressive symptoms, and smoking cessation.

Methods

Following a user-centered design process consisting of competitive analysis, focus groups, and prototype testing, we conducted a single-arm pilot trial of Actify!, a BAT-D app for depressed smokers. Participants used SmokefreeTXT along with Actify! to provide cessation content that had not yet been built into the app for this initial phase of pilot testing. Participants in the trial were current, daily smokers with mild to moderate depressive symptoms. We examined use outcomes for all enrolled participants and process and cessation outcomes at 6 weeks postenrollment for study completers (16/17, 94% retention).

Results

Regarding acceptability, average number of log-ins per participant was 16.6 (SD 13.7), and 63% (10/16) reported being satisfied overall with the app. Posttreatment interviews identified some usability challenges (eg, high perceived burden of planning and scheduling values-based activities). There was a significant decrease in depressive symptoms from baseline to follow-up (mean change in Patient Health Questionnaire–9 scores was –4.5, 95% CI –7.7 to –1.3; P=.01). Additionally, carbon monoxide (CO)-confirmed, 7-day point prevalence abstinence (PPA) at 6-week follow-up was 31% (5/16), and the 30-day PPA was 19% (3/16).

Conclusions

Results demonstrate promising engagement with Actify! and potential for impact on theory-based change processes and cessation outcomes. Preliminary quit rates compare favorably to previous trials of smoking cessation apps for the general population (ie, short-term, self-reported 30-day quit rates in the 8% to 18% range) and a previous trial of face-to-face BAT-D for depressed smokers (ie, CO-confirmed, 7-day PPA rate of 17% at end of treatment).

Effectiveness of an offer of the Smoke Free smartphone application for smoking cessation: protocol for a randomized controlled trial

BACKGROUND AND AIMS

Smartphone applications (apps) hold promise for delivering tobacco smoking cessation support to large numbers of people at low unit cost. Smoke Free is an evidence-informed, widely used app that is highly rated by users. This study aims to assess its effectiveness compared with no support.

DESIGN

Two-arm individually randomized controlled effectiveness trial.

SETTING

Online trial with no restrictions on location.

PARTICIPANTS

English-speaking smokers aged ≥ 18 years willing to make a quit attempt within 4 weeks from initial contact (n = 4990).

MEASUREMENTS

The primary outcome measure is self-reported 26-week continuous smoking abstinence. Secondary outcome measures include quit attempts in the first 4 weeks post-randomization, 12-week continuous smoking abstinence and 26-week continuous smoking abstinence among those who made a quit attempt.

COMMENTS

If it is effective, the Smoke Free smartphone app is an affordable and widely implementable intervention to help smokers to quit.

Smoking cessation with smartphone applications (SWAPP): study protocol for a randomized controlled trial

Background

Tobacco smoking remains one of the biggest public health threats. Smartphone apps offer new promising opportunities for supporting smoking cessation in real-time. The social context of smokers has, however, been neglected in smartphone apps promoting smoking cessation. This randomized controlled trial investigates the effectiveness of a smartphone app in which smokers quit smoking with the help of a social network member.

Methods

This protocol describes the design of a single-blind, two-arm, parallel-group, intensive longitudinal randomized controlled trial. Participants of this study are adult smokers who smoke at least one cigarette per day and intend to quit smoking at a self-set quit date. Blocking as means of group-balanced randomization is used to allocate participants to intervention or control conditions. Both intervention and control group use a smartphone-compatible device for measuring their daily smoking behavior objectively via exhaled carbon monoxide. In addition, the intervention group is instructed to use the SmokeFree Buddy app, a multicomponent app that also facilitates smoking-cessation specific social support from a buddy over a smartphone application. All participants fill out a baseline diary for three consecutive days and are invited to the lab for a background assessment. They subsequently participate in an end-of-day diary phase from 7 days before and until 20 days after a self-set quit date. Six months after the self-set quit date a follow-up diary for three consecutive days takes place. The primary outcome measures are daily self-reported and objectively-assessed smoking abstinence and secondary outcome measures are daily self-reported number of cigarettes smoked.

Discussion

This is the first study examining the effectiveness of a smoking cessation mobile intervention using the SmokeFree Buddy app compared to a control group in a real-life setting around a self-set quit date using a portable objective measure to assess smoking abstinence. Opportunities and challenges with running studies with smoking participants and certain design-related decisions are discussed.

Trial registration

This trial was prospectively registered on 04/04/2018 at ISRCTNregistry: ISRCTN11154315.

Design and Development of Smoking Cessation Apps Based on Smokers' and Providers' Perspectives in China: Survey Study

BACKGROUND

Although there are more than 60 smartphone apps for smoking cessation in China, many of them do not include the content and features that health care professionals and smokers prefer-which may make them impractical, unengaging, and ineffective. Therefore, we investigated both health care providers' and smokers' preferences for features of future smoking cessation apps.

OBJECTIVE

This study aimed to investigate Chinese health care providers' and smokers' desired features of a smoking cessation app, with the goal of providing design recommendations for app designers and researchers.

METHODS

Both Chinese smokers who own smartphones (n=357) and Chinese health care providers (n=224) responded to a survey collecting data on their sociodemographic characteristics and opinions on the importance of 20 smoking cessation app design features studied in previous US research.

RESULTS

Chinese health care providers expressed strong support of smoking cessation apps on a number of attitude indicators (range 153/224, 68.3% to 204/224, 91.1%). They rated nearly all (18/20) features as very or extremely important (range 52.2%-83.4%) and rated nearly all features (17/20) as more important than the smokers did. More than 60% of smokers rated the following 4 features as very or extremely important: allow sharing the process of smoking cessation with family members and friends (216/319, 67.7%), helping smokers track their progress (such as the amount of smoking per day; 213/319, 66.8%), helping with the side effects of medications and nicotine withdrawal symptoms (201/319, 63.0%), and adapting to ongoing needs and interests of smokers (194/319, 60.8%). Contrary to a similar study of US smokers and health care providers, Chinese smokers and providers rated reputation and ability to communicate with family members and friends as important features, whereas Chinese smokers rated privacy and security as less important.

CONCLUSIONS

The design of future smoking cessation and health behavior change apps should consider perspectives of both providers and smokers as well as the role of culture.

Playing Around with Quitting Smoking: A Randomized Pilot Trial of Mobile Games as a Craving Response Strategy

Objective: Strong cravings to smoke are an obstacle to cessation success. Unfortunately, cessation medication and counseling only modestly quell craving. This pilot study was designed to examine the feasibility of mobile games as a response strategy to craving and whether a fully powered trial is warranted. Materials and Methods: Smokers interested in quitting (N = 30) were offered 4 weeks of nicotine patch plus counseling and randomized to quit with (games-on) versus without (games-off) access to 11 commercial mobile games. Outcomes included post-target quit day (TQD) game play, craving, smoking, and quitting. Almost all P's were >0.05; outcomes should be interpreted with caution due to the small N. Results: Of games-on participants (n = 16), one played games ≥80% of days post-TQD (22/28 days); 38% played >1/3 of days; 25% did not play. Games-on participants reported games moderately helped them cope with cravings; M = 3.22 on a scale from 1 (not at all) to 5 (very much). Also, games-on participants showed a slight decrease in craving from baseline to 1-week post-TQD (2.35-2.25 on a 0-5 point-scale), whereas games-off participants showed an increase (2.01-2.53). Games-on participants showed greater decreases in craving after playing a game than after the passage of time (when an app imposed a 2-minute wait period following their game request), but there was little evidence games-on versus games-off participants differed in mean post-TQD cigarettes/day. Games-on participants reported modestly but not significantly higher continuous abstinence through day 28 (31.3% vs. 21.4%). Conclusion: Feasibility results encourage a fully powered trial of this easily disseminable intervention. Clinical Trial Registration: ClinicalTrials.gov NCT02164383.

Pragmatic randomised trial of a smartphone app (NRT2Quit) to improve effectiveness of nicotine replacement therapy in a quit attempt by improving medication adherence: results of a prematurely terminated study

BACKGROUND

Nicotine replacement therapy (NRT) bought over the counter (OTC) appears to be largely ineffective for smoking cessation, which may be partially explained by poor adherence. We developed and evaluated the NRT2Quit smartphone app (for iOS) designed to improve quit attempts with OTC NRT by improving adherence to the medications.

METHODS

This study was a pragmatic double-blind randomised controlled trial with remote recruitment through leaflets distributed to over 300 UK-based community pharmacies. The study recruited adult daily smokers (≥10 cigarettes per day) who bought NRT, wanted to quit smoking, downloaded NTR2Quit and completed the registration process within the app. Participants were automatically randomly assigned within the app to the intervention (full) version of NRT2Quit or to its control (minimal) versions. The primary outcome was biochemically verified 4-week abstinence assessed at 8-week follow-up using Russell Standard criteria and intention to treat. Bayes factors were calculated for the cessation outcome. Secondary outcomes were self-reported abstinence, NRT use, app use and satisfaction with the app.

RESULTS

The study under-recruited. Only 41 participants (3.5% of the target sample) were randomly assigned to NRT2Quit (n = 16) or the control (n = 25) app versions between March 2015 and September 2016. The follow-up rate was 51.2%. The intervention participants had numerically higher biochemically verified quit rates (25.0% versus 8.0%, P = 0.19, odds ratio = 3.83, 0.61-24.02). The calculated Bayes factor, 1.92, showed that the data were insensitive to test for the hypothesis that the intervention app version aided cessation. The intervention participants had higher median logins (2.5 versus 0, P = 0.01) and were more likely to use NRT at follow-up (100.0% versus 28.6%, P = 0.03) and recommend NRT2Quit to others (100.0% versus 28.6%, P = 0.01).

CONCLUSIONS

Despite very low recruitment, there was preliminary but inconclusive evidence that NRT2Quit may improve short-term abstinence and adherence among smokers using NRT. Well-powered studies on NRT2Quit are needed, but different recruitment methods will be required to engage smokers through community pharmacies or other channels.

TRIAL REGISTRATION

ISRCTN ISRCTN33423896 , prospectively registered on 22 March 2015.

Randomized factorial experiment of components of the SmokeFree Baby smartphone application to aid smoking cessation in pregnancy

Smartphone applications (apps) might be able to reach pregnant smokers who do not engage with face-to-face support. However, we do not know how far pregnant smokers will engage with smoking cessation apps or what components are likely to be effective. This study aimed to assess pregnant smokers' engagement with the SmokeFree Baby app (v1) and to assess the short-term efficacy of selected components ("modules") for smoking abstinence. Positive outcomes would provide a basis for further development and evaluation. SmokeFree Baby was developed drawing on behavior change theories and relevant evidence. Pregnant smokers (18+) who were interested in quitting and set a quit date were recruited. Following multiphase optimization development principles, participants (N = 565) were randomly allocated to one of 32 (2 × 2 × 2 × 2 × 2) experimental groups in a full factorial design to evaluate five modules (each in minimal and full version: identity, health information, stress management, face-to-face support, and behavioral substitution). Measures of engagement included duration and frequency of engagement with the app. Smoking abstinence was measured by self-reported number of smoke-free days up to 4 weeks from the quit date. Participants engaged with the app for a mean of 4.5 days (SD = 8.5) and logged in a mean of 2.9 times (SD = 3.1). Main effects of the modules on the number of smoke-free days were not statistically significant (identity: p = .782, health information: p = .905, stress management: p = .103, face-to-face support: p = .397, behavioral substitution: p = .945). Despite systematic development and usability testing, engagement with SmokeFree Baby (v1) was low and the app did not appear to increase smoking abstinence during pregnancy.

A Pilot Randomized Controlled Trial of a Web-Based Growth Mindset Intervention to Enhance the Effectiveness of a Smartphone App for Smoking Cessation

BACKGROUND

Although smartphone apps have shown promise for smoking cessation, there is a need to enhance their low engagement rates. This study evaluated the application of the growth mindset theory, which has demonstrated the potential to improve persistence in behavior change in other domains, as a means to improve engagement and cessation.

OBJECTIVE

This study aimed to explore the feasibility, utility, and efficacy of a Web-based growth mindset intervention for addiction when used alongside a smoking cessation app.

METHODS

Daily smokers (N=398) were all recruited on the Web and randomly assigned to receive either a cessation app alone or the app plus a Web-delivered growth mindset intervention. The primary outcome was engagement, that is, the number of log-ins to the smoking cessation app. The secondary outcome was 30-day point prevalence abstinence at 2-month follow-up collected through a Web-based survey.

RESULTS

The 2-month outcome data retention rate was 91.5% (364/398). In addition, 77.9% (310/398) of the participants in the experimental arm viewed at least 1 page of their growth mindset intervention, and 21.1% (84/398) of the group viewed all the growth mindset intervention. The intention-to-treat analysis did not show statistically significant differences between the experimental and comparison arms on log-ins to the app (19.46 vs 21.61; P=.38). The experimental arm had cessation rates, which trended higher than the comparison arm (17% vs 13%; P=.10). The modified intent-to-treat analysis, including only participants who used their assigned intervention at least once (n=115 in experimental group and n=151 in the control group), showed that the experimental arm had a similar number of log-ins (32.31 vs 28.48; P=.55) but significantly higher cessation rates (21% vs 13%; P=.03) than the comparison arm.

CONCLUSIONS

A growth mindset intervention for addiction did not increase engagement rates, although it may increase cessation rates when used alongside a smartphone app for smoking cessation. Future research is required to refine the intervention and assess efficacy with long-term follow-up to evaluate the efficacy of the mindset intervention.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03174730; https://clinicaltrials.gov/ct2/show/NCT03174730.

Lessons learned from unsuccessful use of personal carbon monoxide monitors to remotely assess abstinence in a pragmatic trial of a smartphone stop smoking app - A secondary analysis

INTRODUCTION

Verifying abstinence remotely in trials of digital cessation interventions remains a major challenge. This study reports on using personal carbon monoxide (CO) monitors to assess abstinence in a pragmatic trial of a standalone cessation app involving automated recruitment with no researcher contact.

METHODS

The study involved secondary data analysis of remote CO testing in a randomized trial (ISRCTN10548241) comparing two versions of a cessation app (BupaQuit). Trial participants were adult UK-based smokers interested in quitting, who were recruited online (02/2015-03/2016). Participants were followed-up through the app, email or phone at 4 weeks. Fifty-nine participants reporting not smoking were posted a personal CO monitor with instructions, and emailed two reminders. The monitors required installing software on a Windows PC. Participants were not reimbursed but retained the device. We recorded the proportion of CO tests returned, test results, self-reported ease of use, correct use, acceptability, and reasons for missing results.

RESULTS

Fifteen (25.4%) CO results were returned, of which 86.6% were <10 ppm and 53.3% were <5 ppm, indicating abstinence (corresponding to 20.9% and 12.9% of all trial participants self-reporting abstinence, respectively). These 15 participants found the test easy, acceptable and believed they conducted it correctly. Eight (18.2%) of the missing results were accounted for, including no access to a Windows PC, barriers to receiving packages, and unwillingness to share results.

CONCLUSION

Remote validation using personal CO monitors may not yet be feasible in pragmatic studies of cessation apps in which participants are recruited with no reimbursement or direct contact with researchers.

Mobile Applications for the Treatment of Tobacco Use and Dependence

PURPOSE OF REVIEW

Smoking remains a leading preventable cause of premature death in the world; thus, developing effective and scalable smoking cessation interventions is crucial. This review uses the Obesity-Related Behavioral Intervention Trials (ORBIT) model for early phase development of behavioral interventions to conceptually organize the state of research of mobile applications (apps) for smoking cessation, briefly highlight their technical and theory-based components, and describe available data on efficacy and effectiveness.

RECENT FINDINGS

Our review suggests that there is a need for more programmatic efforts in the development of mobile applications for smoking cessation, though it is promising that more studies are reporting early phase research such as user-centered design. We identified and described the app features used to implement smoking cessation interventions, and found that the majority of the apps studied used a limited number of mechanisms of intervention delivery, though more effort is needed to link specific app features with clinical outcomes. Similar to earlier reviews, we found that few apps have yet been tested in large well-controlled clinical trials, although progress is being made in reporting transparency with protocol papers and clinical trial registration.

SUMMARY

ORBIT is an effective model to summarize and guide research on smartphone apps for smoking cessation. Continued improvements in early phase research and app design should accelerate the progress of research in mobile apps for smoking cessation.

A content analysis of free smoking cessation mobile applications in the USA

Aims

To evaluate the quality and content of free smoking cessation apps and assess their adherence to the US Public Health Service guideline for treating tobacco use and dependence.

Methods

In total 180 apps were downloaded from the App Store and Google Play Store in January 2018; the top-ranking 30 apps were retrieved for the search terms: ‘smoking cessation’, ‘quit smoking’, ‘stop smoking’. Technical quality was rated using the Mobile Application Rating Scale (MARS) and by assessing other characteristics, behavioral change strategies and adherence to the 5As.

Results/findings

A total 67 free-to-download apps were identified for full review (n = 40 from the Apple App Store and n = 27 from the Google Play Store). The average MARS score was 16.2/19.0: Engagement (3.3/5.0), Functionality (4.4/5.0), Aesthetics (4.0/5.0), and Information (2.6/5.0). Overall, 43 apps allowed sharing, 12 allowed for an app community, and five required a password. The following features were observed: assessment (n = 51), feedback (n = 38), information/education (n = 45), monitoring (n = 52), and goal setting (n = 23). Significant differences were found among apps adhering to the 5As: Ask (n = 44), Advise (n = 54), Assess (n = 30), Assist (n = 62), and Arrange (n = 0).

Conclusions

Given the growth in smoking cessation apps, future efforts should focus on improving their technical quality and adherence to the 5As.

Process Evaluation of a Medical Student-Delivered Smoking Prevention Program for Secondary Schools: Protocol for the Education Against Tobacco Cluster Randomized Trial

Background

Most smokers start smoking during their early adolescence under the impression that smoking entails positive attributes. Given the addictive nature of cigarettes, however, many of them might end up as long-term smokers and suffering from tobacco-related diseases. To prevent tobacco use among adolescents, the large international medical students’ network Education Against Tobacco (EAT) educates more than 40,000 secondary school students per year in the classroom setting, using evidence-based self-developed apps and strategies.

Objective

This study aimed to evaluate the long-term effectiveness of the school-based EAT intervention in reducing smoking prevalence among seventh-grade students in Germany. Additionally, we aimed to improve the intervention by drawing conclusions from our process evaluation.

Methods

We conduct a cluster-randomized controlled trial with measurements at baseline and 9, 16, and 24 months postintervention via paper-and-pencil questionnaires administered by teachers. The study groups consist of randomized schools receiving the 2016 EAT curriculum and control schools with comparable baseline data (no intervention). The primary outcome is the difference of change in smoking prevalence between the intervention and control groups at the 24-month follow-up. Secondary outcomes are between-group differences of changes in smoking-related attitudes and the number of new smokers, quitters, and never-smokers.

Results

A total of 11,268 students of both sexes, with an average age of 12.32 years, in seventh grade of 144 secondary schools in Germany were included at baseline. The prevalence of cigarette smoking in our sample was 2.6%. The process evaluation surveys were filled out by 324 medical student volunteers, 63 medical student supervisors, 4896 students, and 141 teachers.

Conclusions

The EAT cluster randomized trial is the largest school-based tobacco-prevention study in Germany conducted to date. Its results will provide important insights with regards to the effectiveness of medical student–delivered smoking prevention programs at school.

International Registered Report Identifier (IRRID)

DERR1-10.2196/13508

Mass media promotion of a smartphone smoking cessation app: modelled health and cost-saving impacts

BACKGROUND

Smartphones are increasingly available and some high quality apps are available for smoking cessation. However, the cost-effectiveness of promoting such apps has never been studied. We therefore aimed to estimate the health gain, inequality impacts and cost-utility from a five-year promotion campaign of a smoking cessation smartphone app compared to business-as-usual (no app use for quitting).

METHODS

A well-established Markov macro-simulation model utilising a multi-state life-table was adapted to the intervention (lifetime horizon, 3% discount rate). The setting was the New Zealand (NZ) population (N = 4.4 million). The intervention effect size was from a multi-country randomised trial: relative risk for quitting at 6 months = 2.23 (95%CI: 1.08 to 4.77), albeit subsequently adjusted to consider long-term relapse. Intervention costs were based on NZ mass media promotion data and the NZ cost of attracting a smoker to smoking cessation services (NZ$64 per person).

RESULTS

The five-year intervention was estimated to generate 6760 QALYs (95%UI: 5420 to 8420) over the remaining lifetime of the population. For Māori (Indigenous population) there was 2.8 times the per capita age-standardised QALY gain relative to non-Māori. The intervention was also estimated to be cost-saving to the health system (saving NZ$115 million [m], 95%UI: 72.5m to 171m; US$81.8m). The cost-saving aspect of the intervention was maintained in scenario and sensitivity analyses where the discount rate was doubled to 6%, the effect size halved, and the intervention run for just 1 year.

CONCLUSIONS

This study provides modelling-level evidence that mass-media promotion of a smartphone app for smoking cessation could generate health gain, reduce ethnic inequalities in health and save health system costs. Nevertheless, there are other tobacco control measures which generate considerably larger health gains and cost-savings such as raising tobacco taxes.

Comparison of Developers' and End-Users' Perspectives About Smoking Cessation Support Through the Crush the Crave App

Background

High smoking rates among end-users, combined with their high rates of app use, render this age group as a particularly captive audience for quit smoking apps. There is emerging evidence that apps are an effective way to support smoking cessation among end-users. How the expectations behind the design of apps align with the needs and preferences of end-users, and if this differs by gender, is poorly understood, limiting the ability to evaluate and scale these interventions.

Objective

The objective of this qualitative case study was to detail how the overall design approach of Crush the Crave (CTC), a quit smoking app that targets end-users, compares with young adult women’s and men’s perspectives and experiences, with consideration for the influence of gender.

Methods

Semistructured interviews were conducted with 15 developers involved in the development of CTC and 31 young adult CTC users. Data were analyzed inductively to derive thematic findings of the perceived pros and cons of CTC by both developers and end-users. Findings were grouped under 4 categories (1) technology and platforms utilized for the app, (2) foundation of app content, (3) underlying focus of the app, and (4) look, feel and functionality of the app.

Results

Under the category, technology and platforms utilized for the app, it was found that both developers and end-users agreed that apps aligned with the needs and preferences of young adult smokers. Major limitations with the technology identified by end-users were the frequent “glitches” and requirement for internet or data. For the category, foundation of app content,developers agreed that the strength of CTC was in its strong evidence-base. What mattered to end-users, however, was that the content was packaged positively, focusing on the benefits of quitting versus the consequences of smoking. It was found under the category, underlying focus of the app, that the individually-led focus of the app resonated with both developers and end-users, especially young men. Under the final category, look, feel and functionality of the app, it was found that developers were very positive about the app's aesthetics but end-users thought that the aesthetics incited a negative effect. Also, while end-users found it easy to use, they did not find the app intuitive. Finally, end-users thought that, because the app functions were largely based on a user’s quit date versus their ongoing efforts, this often lent to unmeaningful data.

Conclusions

The current study findings highlight the importance of understanding multiple perspectives of stakeholders involved in a mobile-based intervention. By gathering the viewpoints of developers and end-users, both problematic and effective approaches that underlie development goals were revealed as a means of informing the development, implementation, and evaluation of future electronic health (eHealth) interventions.

Impact of a Novel Smartphone App (CureApp Smoking Cessation) on Nicotine Dependence: Prospective Single-Arm Interventional Pilot Study

BACKGROUND

Mobile apps have been considered to provide active and continuous support for smoking cessation. However, it is yet to be known whether a smoking cessation smartphone app improves long-term abstinence rates in nicotine-dependent patients.

OBJECTIVE

This study aimed to evaluate the long-term abstinence effect of a novel smartphone app, CureApp Smoking Cessation (CASC), in patients with nicotine dependence.

METHODS

In this prospective, interventional, multicenter, single-arm study, we provided the CASC app to all the participants, who used it daily for 24 weeks. The CASC app includes features to maximize the therapeutic effect of pharmacological therapies and counseling at outpatient clinics for smoking cessation. The primary endpoint was a continuous abstinence rate (CAR) from weeks 9 to 24, whereas secondary endpoints were CARs from weeks 9 to 12 and 9 to 52.

RESULTS

Of the 56 adult smokers recruited, 1 did not download the app; therefore, 55 participants constituted the full analysis sample. The CAR from weeks 9 to 24 was 64% (35/55, 95% CI 51%-76%), whereas the CARs from weeks 9 to 12 and 9 to 52 were 76% (42/55, 95% CI 65%-88%) and 58% (32/55, 95% CI 46%-71%), respectively. These CARs were better than the results of the national survey on outpatient clinics with regard to smoking cessation under the National Health Insurance Program and that of the varenicline phase 3 trial in Japan and the United States. There was only 1 participant who dropped out during the 12 weeks of the treatment period. This treatment decreased the scores related to withdrawal and craving symptoms.

CONCLUSIONS

The addition of CASC to usual smoking cessation therapies resulted in high CARs, high patient retention rates, and improvement of cessation-related symptoms. The smartphone app CASC is a feasible and useful tool to help long-term continuous abstinence that can be combined with a standard smoking cessation treatment program.