Dataset Information

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

ABSTRACT:

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 M?ori (Indigenous population) there was 2.8 times the per capita age-standardised QALY gain relative to non-M?ori. 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.

SUBMITTER: Nghiem N

PROVIDER: S-EPMC6408783 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Publications

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

Nghiem Nhung N Leung William W Cleghorn Christine C Blakely Tony T Wilson Nick N

BMC public health 20190308 1

<h4>Background</h4>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).<h4>Methods</h4>A well-established Markov macro-simulation model utilising a multi-st ...[more]

PMID: 30849943

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

Project description:Emerging evidence supports the use of smartphone apps for smoking cessation, especially in young adults given their high smoking rates and high smartphone ownership rates. Although evaluative evidence is encouraging for supporting smoking cessation, there remains a paucity of research describing the design and development processes of mobile health (mHealth) interventions.The aim of this paper was to describe the process of developing Crush the Crave (CTC), an evidence-informed app to support smoking cessation in young adults, and the results of a formative evaluation of app usage behavior, as part of a broader program of research that seeks to establish the effectiveness of the CTC app.The Spiral Technology Action Research (STAR) 5-cycle model (listen, plan, do, act, and study) was employed to guide the development, implementation, and dissemination of CTC. The approach to development and formative evaluation included focus groups with young adult smokers (n=78) across 2 phases, analysis of the content of existing apps, 2 sessions with content experts, and Google Analytics to assess user behavior during a 12-month pilot.LISTEN-focus groups revealed young adult smoker preferences of (1) positive reinforcement, (2) personalization, (3) social support, (4) quit support, (5) tracking the behavior, and (6) tracking quit benefits. PLAN-informed by evidence for smoking cessation, young adult preferences and an assessment of popular cessation apps, content experts produced a mind map and a storyboard describing app content and structure. DO-focus groups with young adult smokers provided feedback on the first version of the app with opinions on content and suggestions for improvement such as providing alerts and distractions from craving. ACT-refinements were made, and app content was organized using the 4 key design components informed by principles of persuasive technology for behavior change: credibility, task support, dialogue support, and social support. CTC was launched in April 2013 and piloted from the period July 2013 to June 2014 where 1987 Android users had 18,567 sessions, resulting in 59,384 page views and 89.58% (1780/1987) of users returning within the same day to use CTC. STUDY-a pragmatic randomized controlled trial of CTC was launched in August 2014 to demonstrate that including mHealth technology as a population-based intervention can help young adult smokers to quit. The results of this phase will be presented in a subsequent publication.CTC is one of the first smoking cessation apps designed to meet the needs of young adult smokers. The development was informed by the inclusion of young adults in the design and the systematic application of multiple stakeholder input, scientific evidence, and theory. The STAR model approach was followed from the beginning of intervention development, which should facilitate optimization of mHealth interventions in the future.ClinicalTrials.gov NCT01983150; http://clinicaltrials.gov/ct2/show/NCT01983150 (Archived by WebCite at http://www.webcitation.org/6VGyc0W0i).

Project description:BACKGROUND:Smoking rates of Australians with severe mental illness (SMI) are disproportionately higher than the general population. Despite the rapid growth in mobile health (mHealth) apps, limited evidence exists to inform their design for SMI populations. OBJECTIVE:This study aimed to explore the feasibility, acceptability, and utility of adapting a novel smoking cessation app (Kick.it) to assist smokers with SMI to prevent smoking relapse and quit. METHODS:Using co-design, two in-depth interviews with 12 adult smokers and ex-smokers with SMI were conducted in this qualitative study. Stage 1 interviews explored participants' smoking-related experiences and perceptions of social support for smoking cessation, informed the development of the stage 2 interview schedule, and provided context for participants' responses to the second interview. Stage 2 interviews explored participants' perceptions of the feasibility, utility, and acceptability of the app features for SMI populations. RESULTS:People with SMI perceived mHealth interventions to support their quit smoking attempts as feasible, acceptable, and useful. Key emerging themes included personalization of the app to users' psychosocial needs, a caring app to mediate self-esteem and self-efficacy, an app that normalizes smoking relapse and multiple quit attempts, a strong focus on user experience to improve usability, and a social network to enhance social support for smoking cessation. CONCLUSIONS:This study gained an in-depth understanding of the lived experiences of smoking and quitting among people with SMI and their perception of the Kick.it app features to help inform the tailoring of the app. Specific program tailoring is required to assist them in navigating the complex interactions between mental illness and smoking in relation to their psychosocial well-being and capacity to quit. This study describes the adaptations required for the Kick.it app to meet the specific needs and preferences of people with SMI. Results of this study will guide the tailoring of the Kick.it app for SMI populations. The study findings can also inform a co-design process for the future development and design of smoking cessation apps for SMI populations.

Project description:BackgroundLittle is known about how individuals engage over time with smartphone app interventions and whether this engagement predicts health outcomes.ObjectiveIn the context of a randomized trial comparing 2 smartphone apps for smoking cessation, this study aimed to determine distinct groups of smartphone app log-in trajectories over a 6-month period, their association with smoking cessation outcomes at 12 months, and baseline user characteristics that predict data-driven trajectory group membership.MethodsFunctional clustering of 182 consecutive days of smoothed log-in data from both arms of a large (N=2415) randomized trial of 2 smartphone apps for smoking cessation (iCanQuit and QuitGuide) was used to identify distinct trajectory groups. Logistic regression was used to determine the association of group membership with the primary outcome of 30-day point prevalence of smoking abstinence at 12 months. Finally, the baseline characteristics associated with group membership were examined using logistic and multinomial logistic regression. The analyses were conducted separately for each app.ResultsFor iCanQuit, participants were clustered into 3 groups: "1-week users" (610/1069, 57.06%), "4-week users" (303/1069, 28.34%), and "26-week users" (156/1069, 14.59%). For smoking cessation rates at the 12-month follow-up, compared with 1-week users, 4-week users had 50% higher odds of cessation (30% vs 23%; odds ratio [OR] 1.50, 95% CI 1.05-2.14; P=.03), whereas 26-week users had 397% higher odds (56% vs 23%; OR 4.97, 95% CI 3.31-7.52; P<.001). For QuitGuide, participants were clustered into 2 groups: "1-week users" (695/1064, 65.32%) and "3-week users" (369/1064, 34.68%). The difference in the odds of being abstinent at 12 months for 3-week users versus 1-week users was minimal (23% vs 21%; OR 1.16, 95% CI 0.84-1.62; P=.37). Different baseline characteristics predicted the trajectory group membership for each app.ConclusionsPatterns of 1-, 3-, and 4-week smartphone app use for smoking cessation may be common in how people engage in digital health interventions. There were significantly higher odds of quitting smoking among 4-week users and especially among 26-week users of the iCanQuit app. To improve study outcomes, strategies for detecting users who disengage early from these interventions (1-week users) and proactively offering them a more intensive intervention could be fruitful.

Project description:IntroductionMindfulness 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.MethodsA 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).ResultsNo 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).ConclusionsAlthough 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.ImplicationsThis 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 registrationClinicaltrials.gov NCT02134509.

Project description:WHO supports the harnessing of mobile technologies to improve access to smoking cessation services. As such, this study evaluated the effectiveness of smoking cessation services provided by community pharmacists using PharmQuit compared with standard care. The study was a prospective, multicenter, randomized controlled trial that included 156 participants who were 18 years or older and smoked at least one cigarette daily for a month, were ready to quit, willing to participate, and had a smartphone. The study was performed at seven community pharmacies in three provinces in Thailand. Participants were allocated to the intervention (n = 78) and control groups (n = 78). Both groups received the usual smoking cessation services with pharmacotherapy and counseling from community pharmacists for 6 months. The intervention group received PharmQuit as an additional service. Both groups were scheduled for follow-up visits on days 7, 14, 30, 60, 120, and 180. The primary outcome was continuous abstinence rate on day 180. The secondary outcomes included 7-day point abstinence rate, number of cigarettes smoked per day, exhaled carbon monoxide levels, adherence rate to the program, and satisfaction with PharmQuit. An analysis using the intent-to-treat principle was performed. Smoking cessation rates and the number of cigarettes smoked per day were significantly higher during the follow-up visits in both groups (p < 0.05). However, there were no statistically significant differences between the two groups. The adherence rate to the smoking cessation program was higher in the intervention group than in the control group (74 days vs. 60 days, p > 0.05). The results showed the benefits of the contribution of community pharmacists. Although the inclusion of PharmQuit did not yield better results than pharmacists' counselling alone, it may help obtain better adherence to smoking cessation programs. Trial registration: Thai Clinical Trials Registry: TCTR20200925004 on September 25, 2020 -retrospectively registered, http://www.clinicaltrials.in.th/index.php?tp=regtrials&menu=trialsearch&smenu=fulltext&task=search&task2=view1&id=6841.

Project description:BACKGROUND:Mobile health (mHealth) apps have the potential to increase smoking cessation, but little research has been conducted with Aboriginal communities in Australia. OBJECTIVE:We conducted a pilot study to assess the feasibility and acceptability and explore the effectiveness of a novel mHealth app to assist Aboriginal people to quit smoking. METHODS:A pilot randomized controlled trial (RCT) and process evaluation comprising usage analytics data and in-depth interviews was conducted. Current Aboriginal smokers (>16 years old), who were willing to make a quit attempt in the next month, were recruited from Aboriginal Community Controlled Health Services and a government telephone coaching service. The intervention was a multifaceted Android or iOS app comprising a personalized profile and quit plan, text and in-app motivational messages, and a challenge feature allowing users to compete with others. The comparator was usual cessation support services. Outcome data collection and analysis were conducted blinded to treatment allocation. The primary outcome was self-reported continuous smoking abstinence verified by carbon monoxide breath testing at 6 months. Secondary outcomes included point prevalence of abstinence and use of smoking cessation therapies and services. RESULTS:A total of 49 participants were recruited. Competing service delivery priorities, the lack of resources for research, and lack of support for randomization to a control group were the major recruitment barriers. At baseline, 23/49 (47%) of participants had tried to quit in recent weeks. At 6-month follow-up, only 1 participant (intervention arm) was abstinent. The process evaluation highlighted low to moderate app usage (3-10 new users per month and 4-8 returning users per month), an average of 2.9 sessions per user per month and 6.3 min per session. Key themes from interviews with intervention participants (n=15) included the following: (1) the powerful influence of prevailing social norms around acceptability of smoking; (2) high usage of mobile devices for phone, text, and social media but very low use of other smartphone apps; (3) the role of family and social group support in supporting quit attempts; and (4) low awareness and utilization of smoking cessation support services. Despite the broad acceptability of the app, participants also recommended technical improvements to improve functionality, greater customization of text messages, integration with existing social media platforms, and gamification features. CONCLUSIONS:Smoking cessation apps need to be integrated with commonly used functions of mobile phones and draw on social networks to support their use. Although they have the potential to increase utilization of cessation support services and treatments, more research is needed to identify optimal implementation models. Robust evaluation is critical to determine their impact; however, an RCT design may not be feasible in this setting. TRIAL REGISTRATION:Australian and New Zealand Clinical Trials Registry ACTRN12616001550493; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371792 (Archived by WebCite at http://www.webcitation.org/76TiV7HA6).

Dataset Information

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

Background

Methods

Results

Conclusions

Publications

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

Similar Datasets

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