Effectiveness of eHealth Smoking Cessation Interventions: Systematic Review and Meta-Analysis

Initial assessment of a novel smoking cessation program integrating app-based behavioral therapy and an electronic cigarette: results of a pilot study

BACKGROUND

Detrimental smoking-related health outcomes warrant the investigation of novel smoking cessation interventions; the cessation program nuumi integrates digital behavioral therapy and an electronic cigarette (EC).

OBJECTIVE

The relationship between program participation and smoking cessation among adults who smoke and are motivated to quit was investigated, as well as program acceptability, changes in smoking-related outcomes, including cigarettes per day (CPD), urges to smoke and psychophysiological health variables (perceived stress, mindfulness, cessation-related self-efficacy, life satisfaction, subjective psychophysiological health) and their associations with smoking cessation.

METHODS

A prospective 6-month single-arm pilot study was conducted; 71 adults who smoked and were motivated to quit received a cognitive behavioral therapy (CBT) app, a closed-system EC, and pods containing decreasing nicotine concentrations. Online surveys were issued at baseline, and at 4, 8, 12, and 24 weeks post-baseline. Intention-to-treat (ITT) and complete-case analyses were conducted to assess self-reported 7-day point prevalence of smoking abstinence (PPA; primary outcome), 30-day PPA, and repeated PPA. T-tests and logistic regressions were used to assess changes in secondary outcomes CPD, urges to smoke, and psychophysiological health variables by smoking status at 12 and 24 weeks, and their relationship with cessation.

RESULTS

Per ITT, self-reported abstinence rates were high at 12 weeks (39.4%), and 24 weeks (32.4%), as was 30-day PPA of 32.4% at both 12 and 24 weeks. Repeated PPA per ITT was 22.5% at both 12 and 24 weeks. Non-abstinent participants significantly reduced their CPD at 12 weeks (t(34) = 6.12, p < 0.001), and at 24 weeks (t(30) = 6.38, p < 0.001). Urges to smoke and perceived stress decreased, and mindfulness, cessation-related self-efficacy, life satisfaction and subjective psychophysiological health increased significantly (all ps < 0.05), predominantly in individuals who reported abstinence. Lower urges to smoke, lower perceived stress, and higher self-efficacy and subjective mental health were related to greater odds of cessation at 24 weeks (all ps < 0.05). Most participants rated the program as highly (43%) or moderately (54%) acceptable.

DISCUSSION

Program participation seems to support cessation and improvements in smoking-related outcomes, but adjustments to the program may be needed to improve engagement and acceptability. Findings may inform the development of future trials and cessation programs.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00032652, registered prospectively 09/15/2023, https://drks.de/search/de/trial/DRKS00032652.

[Expert consensus for the organization of smoking management in Spain]

OBJECTIVE

To generate a cost-effective healthcare model for the management of smoking in Spain.

MATERIAL AND METHODS

This was a qualitative study based on nominal group methodology and a literature review. Nine tobacco experts (3 pulmonologists, 3 primary care physicians, and 3 community pharmacists) analysed the current smoking care context and available evidence on interventions. Based on this information, they generated a healthcare model for the management of smoking.

RESULTS

A total of 11 general principles were agreed upon, including, for example, the recognition of smoking as a chronic disease, the need for a comprehensive, coordinated approach adjusted to the characteristics and needs of the smokers, or the training of health care professionals on smoking cessation. Two proposed levels of smoking care were established and described (characteristics, competencies, resources, etc.); one is non-specialized (primary care, hospital care and community pharmacy) and another is specialized (smoking units). The objective of the non-specialized level is to identify the smoker, establish the diagnosis, evaluate the patients, and provide at least a brief intervention. The non-specialized level provides highly specialized comprehensive assistance to smokers with special characteristics. The document summarizes the evidence of the main interventions on smoking and has recommendations and care algorithms (actions in the patients' first and subsequent visits and referral criteria).

CONCLUSIONS

Smoking in Spain requires a comprehensive, structured, interdisciplinary, coordinated, and efficient approach adapted to the characteristics and needs of the smokers.

Trend of Metabolic Syndrome Indicators in Working Korean Women According to Smoking Status and Workplace Size: A Population-Based Retrospective Longitudinal Study

OBJECTIVE

Smoking, a risk factor for metabolic syndrome, is associated with stress relief and pleasure among women, which can hinder efforts to quit smoking, particularly in workplaces. We investigated the metabolic syndrome indicators among working Korean women based on smoking status and workplace size to devise tailored smoking cessation policies.

DESIGN

Retrospective longitudinal study.

SAMPLE

Data from 53,126 working Korean women aged 15-64 years were collected between 2009 and 2015.

MEASUREMENTS

Data were collected from the Female Employees Database derived from the National Health Insurance Service. To assess the trend of metabolic syndrome indicators among working Korean women according to smoking status and workplace size, repeated-measures analysis of variance was used.

RESULTS

Significant interactions were found between time and group for waist circumference (WC), diastolic blood pressure (DBP), and fasting glucose (FG) levels. Trends of metabolic syndrome were more prevalent in small- and medium-sized enterprises (SMSEs) than in large-sized enterprises (LSEs). Current smokers in the LSE group had the highest WC, triglyceride, systolic blood pressure, and FG values.

CONCLUSIONS

These insights may be valuable for devising policies and interventions to improve metabolic health among women working in SMSEs and current smokers in LSEs.

Behavior Change Support Systems for Self-Treating Procrastination: Systematic Search in App Stores and Analysis of Motivational Design Archetypes

BACKGROUND

The phenomenon of procrastination refers to an individual's conscious decision to postpone the completion of tasks despite being aware of its adverse consequences in the future. Extant research in this field shows that procrastination is associated with increased levels of anxiety and stress and the likelihood of developing depression and calls for the development of suitable interventions that support individuals in making lasting positive changes to their procrastination behaviors. In parallel, practice has produced a plethora of behavior change support systems (BCSSs) that aim to provide a low-threshold, accessible alternative to in-person therapeutic approaches. Most of these BCSSs can be considered motivational BCSSs that combine functional, utilitarian components with hedonic and eudaimonic design elements to empower self-treatment. Although early studies have suggested the potential benefits of such BCSSs, research on understanding their specific design characteristics and support of individuals in self-treating procrastination is still in its infancy.

OBJECTIVE

In response to this gap between practice and research, we aimed to analyze and systemize the multitude of practical design efforts in motivational BCSSs for the self-treatment of procrastination and identify the main design archetypes that have emerged.

METHODS

We conducted a 3-step research approach. First, we identified 127 behavior change support apps for procrastination through a systematic screening process in the German and US Apple App Store and Google Play Store. Second, we systematically coded the identified apps in terms of the behavior change techniques targeted by their functional design and hedonic or eudaimonic design elements. Third, we conducted a 2-step cluster analysis to identify archetypes of motivational design in behavior change support apps to combat procrastination.

RESULTS

A variety of motivational designs have been developed and implemented in practice, and our analysis identified five main archetypes: (1) structured progress monitor, (2) self-improvement guide, (3) productivity adventure, (4) emotional wellness coach, and (5) social focus companion. The identified archetypes target different psychological determinants of procrastination and successfully use a variety of hedonic and eudaimonic design elements that extend beyond the current state of research.

CONCLUSIONS

The results of our study provide a foundation for future research endeavors that aim to examine the comparative effects of motivational design archetypes and develop more effective interventions tailored to individual needs. For practitioners, the findings reveal the contemporary design space of motivational BCSSs to support the self-treatment of procrastination and may serve as blueprints that can guide the design of future systems. For individuals seeking support and health professionals treating procrastination, our study systemizes the landscape of apps, thereby facilitating the selection of one that best aligns with the patient's individual needs.

Prevalence of Popular Smoking Cessation Aids in England and Associations With Quit Success

Importance

A wide range of medications, noncombustible nicotine products, behavioral support, and alternative treatments are available in England to help people stop smoking. Understanding their effectiveness outside of clinical trial settings can support informed decision-making.

Objectives

To provide up-to-date estimates of the prevalence of different smoking cessation aids and associations with quit success and to explore moderation by socioeconomic position.

Design, Setting, and Participants

This survey study used data from the Smoking Toolkit Study, a monthly cross-sectional household survey, conducted from 2006 to 2024 in England, UK. Participants were individuals aged at least 16 years who reported trying to quit smoking in the past year. Analyses were conducted from July to November 2024.

Main Outcomes and Measures

The outcome variable was self-reported success in quitting smoking from the start of the most recent quit attempt up to the time of survey (hereafter, quit success). Independent variables were use (yes or no) of the following aids in the most recent attempt: nicotine replacement therapy (NRT), obtained via prescription or over-the-counter; varenicline; bupropion; electronic cigarettes (e-cigarettes); face-to-face behavioral support; telephone support; written self-help materials; websites; smartphone apps; hypnotherapy; Allen Carr's Easyway method; heated tobacco products (HTPs); and nicotine pouches. Covariates included sociodemographic characteristics and features of the quit attempt.

Results

A total of 25 094 participants (mean [SD] age, 38.7 [15.3] years; 51.5% [95% CI, 50.8%-52.2%] men) were included. In 2023 to 2024, the most used aids were e-cigarettes (40.2% [95% CI, 37.6%-42.8%]) and over-the-counter NRT (17.3% [95% CI, 15.3%-19.2%]); 40.8% (95% CI, 38.2%-43.4%) of quit attempts were unaided. While e-cigarette use was associated with higher odds of quit success after adjustment for use of other aids and covariates (odds ratio [OR], 1.95 [95% CI, 1.74-2.17]), use of over-the-counter NRT was not (OR, 1.03 [95% CI, 0.93-1.15]). Other aids positively associated with quit success were websites (used by 4.6% [95% CI, 3.5%-5.7%] in 2023-2024; OR, 1.43 [95% CI, 1.03-1.98]), prescription NRT (used by 4.5% [95% CI, 3.4%-5.5%] in 2023-2024; OR, 1.33 [95% CI, 1.12-1.58]), varenicline (used by 1.1% [95% CI, 0.5%-1.7%] in 2023-2024; OR, 1.80 [95% CI, 1.50-2.18]), and HTPs (used by 0.7% [95% CI, 0.3%-1.1%] in 2023-2024; OR, 2.37 [95% CI, 1.24-4.51]). Face-to-face behavioral support (used by 2.2% [95% CI, 1.5-2.9] in 2023-2024) was associated with higher odds of quit success among those from less advantaged (OR, 1.59 [95% CI, 1.19-2.14]) but not more advantaged (OR, 0.91 [95% CI, 0.65-1.29]) socioeconomic positions. There was not clear evidence of a benefit of any other aid, although some analyses were inconclusive.

Conclusions and Relevance

This cross-sectional study found that while a range of effective smoking cessation aids are available in England, many people tried to quit using less effective forms of support or none at all. Quit success rates could be improved by encouraging people to use more effective methods.

Tales of hope and hesitation: Smoking cessation experts' views on the opportunities and risks of digital behaviour change interventions

Objective

Smoking remains a global health challenge, with 1.14 billion active smokers worldwide. Many of these smokers seek cessation support. The rise of mHealth offers novel intervention methods, providing monitoring and tailored feedback. This study aimed to map the opportunities and challenges of integrating digital behaviour change interventions (mHealth) into smoking cessation practices by understanding professionals' perceptions of these tools.

Methods

A qualitative study was conducted involving semi-structured interviews with 11 experienced smoking cessation professionals in Flanders, Belgium. Data collection occurred between January and April 2023. Inductive thematic analysis was performed to identify key patterns and themes in the experts' views regarding mHealth interventions.

Results

The analysis revealed four primary themes: (1) The Inexorable March of Technology - experts acknowledged the inevitability of technology in smoking cessation but varied in enthusiasm; (2) The Shimmering Mirage of Possibility - technology was viewed as supplementary, offering efficiency and support but limited in depth; (3) The Footnotes to Enthusiasm - experts expressed concerns over privacy, inclusivity, and the potential for technology to displace human care; and (4) The Human Anchor - the irreplaceable role of human connection and therapeutic alliance, which digital tools might not be able to replicate.

Conclusion

Experts believe mHealth interventions can augment smoking cessation support but should not replace human-driven care. A blended approach, integrating digital tools with traditional therapeutic relationships, offers the most promise. Addressing concerns about privacy, inclusivity, and most importantly the limits of digital therapeutic alliances is essential for successful mHealth implementation in smoking cessation.

Don't Forget the Humble Text Message: 25 Years of Text Messaging in Health

Since the early studies exploring the use of SMS text messaging for health intervention, text messaging has played a pivotal role in the advancement of mobile health. As an intervention modality, text messaging has provided vital learnings for the design and delivery of interventions, particularly in low-resource settings. Despite the advances in technology over the last 25 years, text messaging is still being used in largely the same way to deliver health information, behavior change interventions, and support. The strong, consistent evidence for the benefits of this type of intervention has made text messaging a routine part of health interventions around the world. Key to its success is its simplicity, alongside the benefit of being arguably the most accessible form of consumer digital health intervention. Text message interventions are well suited for public health interventions due to their low cost, vast reach, frequent use, high read rates, and ability to be tailored and personalized. Furthermore, the nature of text messaging interventions makes them ideal for the delivery of multilingual, culturally tailored interventions, which is important in the context of increasing cultural diversity in many countries internationally. Indeed, studies assessing text message-based health interventions have shown them to be effective across sociodemographic and ethnic groups and have led to their adoption into national-level health promotion programs. With a growing focus on artificial intelligence, robotics, sensors, and other advances in digital health, there is an opportunity to integrate these technologies into text messaging programs. Simultaneously, it is essential that equity remains at the forefront for digital health researchers, developers, and implementers. Ensuring digital health solutions address inequities in health experienced across the world while taking action to maximize digital inclusion will ensure the true potential of digital health is realized. Text messaging has the potential to continue to play a pivotal role in the delivery of equitable digital health tools to communities around the world for many years to come. Further new technologies can build on the humble text message, leveraging its success to advance the field of digital health. This Viewpoint presents a retrospective of text messaging in health, drawing on the example of text message-based interventions for smoking cessation, and presents evidence for the continued relevance of this mobile health modality in 2025 and beyond.

Predicting Early Dropout in a Digital Tobacco Cessation Intervention: Replication and Extension Study

BACKGROUND

Detecting early dropout from digital interventions is crucial for developing strategies to enhance user retention and improve health-related behavioral outcomes. Bricker and colleagues proposed a single metric that accurately predicted early dropout from 4 digital tobacco cessation interventions based on log-in data in the initial week after registration. Generalization of this method to additional interventions and modalities would strengthen confidence in the approach and facilitate additional research drawing on it to increase user retention.

OBJECTIVE

This study had two research questions (RQ): RQ1-can the study by Bricker and colleagues be replicated using data from a large-scale observational, multimodal intervention to predict early dropout? and RQ2-can first-week engagement patterns identify users at the greatest risk for early dropout, to inform development of potential "rescue" interventions?

METHODS

Data from web users were drawn from EX, a freely available, multimodal digital intervention for tobacco cessation (N=70,265). First-week engagement was operationalized as any website page views or SMS text message responses within 1 week after registration. Early dropout was defined as having no subsequent engagement after that initial week through 1 year. First, a multivariate regression model was used to predict early dropout. Model predictors were dichotomous measures of engagement in each of the initial 6 days (days 2-7) following registration (day 1). Next, 6 univariate regression models were compared in terms of their discrimination ability to predict early dropout. The sole predictor of each model was a dichotomous measure of whether users had reengaged with the intervention by a particular day of the first week (calculated separately for each of 2-7 days).

RESULTS

For RQ1, the area under the receiver operating characteristic curve (AUC) of the multivariate model in predicting dropout after 1 week was 0.72 (95% CI 0.71-0.73), which was within the range of AUC metrics found in the study by Bricker and colleagues. For RQ2, the AUCs of the univariate models increased with each successive day until day 4 (0.66, 95% CI 0.65-0.67). The sensitivity of the models decreased (range 0.79-0.59) and the specificity increased (range 0.48-0.73) with each successive day.

CONCLUSIONS

This study provides independent validation of the use of first-week engagement to predict early dropout, demonstrating that the method generalizes across intervention modalities and engagement metrics. As digital intervention researchers continue to address the challenges of low engagement and early dropout, these results suggest that first-week engagement is a useful construct with predictive validity that is robust across interventions and definitions. Future research should explore the applicability and efficiency of this model to develop interventions to increase retention and improve health behavioral outcomes.

Evaluation of effectiveness and acceptability of a psychological treatment for smoking cessation combined with a smartphone App: A pilot study

Despite the increasing number of mobile-based interventions to quit smoking over the last years, few studies have investigated the efficacy of smoking cessation interventions blended with smartphone Apps. The present pilot study aims to examine the preliminary effectiveness and acceptability of a cognitive-behavioral treatment combined with a smartphone App, compared to the same psychological treatment without the App. The sample comprised 206 treatment-seeking smokers, who were assigned to: 1) an experimental group receiving a cognitive-behavioral intervention combined with the "Non Fumo" App (n = 102), and 2) a control group receiving only the cognitive-behavioral intervention to quit smoking (n = 104). Results concerning the primary outcomes showed no significant differences between conditions in point-prevalence abstinence rates at 12-month follow-up (35.30 % in the experimental group vs. 31.70 % in the control group) and in treatment acceptability. Regarding the secondary outcomes, both groups obtained similar point-prevalence abstinence rates at the end of treatment (61.80 % vs. 65.40 %), at 3-month (42.20 % vs. 45.20 %, respectively) and 6-month follow-ups (37.30 % vs. 37.50 %). No significant differences were found between conditions in prolonged abstinence rates at 6-month (35.3 % vs. 35.6 %) and 12-month follow-ups (30.4 % vs. 26.9 %). Overall, good abstinence rates and treatment acceptability were obtained, although there were no significant differences between conditions. More research is needed to establish clear conclusions about the efficacy of psychological smoking cessation treatments blended with smartphone Apps.

Effectiveness of Applying Green Heart, a Smartphone-Based Self-management Intervention to Control Smoking: A Randomized Clinical Trial

BACKGROUND

Cardiovascular diseases (CVDs) pose a significant global health concern and are the most common cause of death and disability, necessitating preventive interventions targeting modifiable risk factors. Recently, mobile-health technology has been developed to improve the delivery of cardiovascular prevention by risk factor modification. The "Green Heart" mobile application (app) was designed to aid in risk factor control among coronary artery disease (CAD) patients.

METHODS

This parallel-group, single-blinded randomized controlled trial enrolled 1590 CAD patients, including 668 current smokers, randomly assigned to control (paper-based education) and intervention (application-based) groups. The app encompassed three modules targeting smoking cessation, dyslipidemia control, and blood pressure management. This study evaluated the impact of the smoking cessation module on behavioral change among current smokers. Green Heart assesses nicotine dependence, offering personalized quit plans, educational content, motivational messages, and automated progress tracking. The odds of smoking behavior changes during the 24-week follow-up underwent assessment.

RESULTS

The intention-to-treat analysis highlighted significantly elevated rates of smoking cessation and reductions in the intervention group versus the control group. Adherence to the app (per-treatment analysis) also demonstrated significantly more favorable smoking behavior changes among the application users. Logistic regression emphasized higher odds of quitting and reduction in smoking in the application group, showing an odds ratio of 2.14 (95% CI: 1.16-3.97) compared to those not using the app (P=0.015).

CONCLUSION

Our results confirmed that complete adherence to the app for at least 24 weeks was linked to alterations in cigarette smoking behavior among CAD patients. Trial Registration Number: IRCT20221016056204N1.

Pilot Testing of an mHealth App for Tobacco Cessation in People Living With HIV: Protocol for a Pilot Randomized Controlled Trial

BACKGROUND

An estimated 40% of people living with HIV smoke cigarettes. Although smoking rates in the United States have been declining in recent years, people living with HIV continue to smoke cigarettes at twice the rate of the general population. Mobile health (mHealth) technology is an effective tool for people living with a chronic illness, such as HIV, as currently 84% of households in the United States report that they have a smartphone. Although many studies have used mHealth interventions for smoking cessation, few studies have recruited people living with HIV who smoke.

OBJECTIVE

The objective of the pilot randomized controlled trial (RCT) is to examine the feasibility, acceptability, and preliminary efficacy of the Sense2Quit App as a tool for people living with HIV who are motivated to quit smoking.

METHODS

The Sense2Quit study is a 2-arm RCT for people living with HIV who smoke cigarettes (n=60). Participants are randomized to either the active intervention condition, which consists of an 8-week supply of nicotine replacement therapy, standard smoking cessation counseling, and access to the Sense2Quit mobile app and smartwatch, or the control condition, which consists of standard smoking cessation counseling and a referral to the New York State Smokers' Quitline. The Sense2Quit app is a mobile app connected through Bluetooth to a smartwatch that tracks smoking gestures and distinguishes them from other everyday hand movements. In the Sense2Quit app, participants can view their smoking trends, which are recorded through their use of the smartwatch, including how often or how much they smoke and the amount of money that they are spending on cigarettes, watch videos with quitting tips, information, and distractions, play games, set reminders, and communicate with a study team member.

RESULTS

Enrollment of study participants began in March 2023 and is expected to end in October 2023. All data collection is expected to be completed by the end of January 2024. This RCT will test the difference in outcomes between the control and intervention arms. The primary outcome will be the percentage of participants with biochemically verified 7-day point prevalence smoking or tobacco abstinence at their 12-week follow-up. Results from this pilot study will be disseminated to the research community following the completion of all data collection.

CONCLUSIONS

The Sense2Quit study leverages mHealth so that it can help smokers improve their efforts at smoking cessation. Our research has the potential to not only increase quitting rates among people living with HIV who may need a prolonged, tailored intervention but also inform further development of mHealth for people living with HIV. This mHealth study will contribute significant findings to the greater mHealth research community, providing evidence as to how mHealth should be developed and tested among the target population.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05609032; https://clinicaltrials.gov/study/NCT05609032.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/49558.