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

Effectiveness of the QuitSure Smartphone App for Smoking Cessation: Findings of a Prospective Single Arm Trial

BACKGROUND

Digital therapies, especially smartphone apps for active and continuous smoking cessation support, are strongly emerging as an alternative smoking cessation therapy. In the Indian context, there is a growing interest in the use of app-based smoking cessation programs; however, there is limited evidence regarding their effectiveness in achieving long-term continuous abstinence.

OBJECTIVE

This study aimed to evaluate the long-term abstinence effect (up to 30-d abstinence postprogram completion) of a smartphone app, QuitSure, for smoking cessation in active smokers from India.

METHODS

In this prospective single-arm study, participants who signed up for the QuitSure app were enrolled in this study. The primary end point was the prolonged abstinence (PA) rate from weeks 1 to 4 (day 7 to day 30). Furthermore, data for withdrawal symptoms, relapse reasons, and reasons for not continuing the program were also assessed.

RESULTS

The quit rate was calculated considering only the participants who followed up and completed the survey sent to them (per protocol) at day 7 and at day 30, respectively. The PA rate at day 7 was found to be 64.5% (111/172; 95% CI 56% to 72%), and the PA rate at day 30 was found to be 55.8% (72/129; 95% CI 45% to 65%). Within the 7-day abstinence period, 60.4% (67/111) of the participants did not have any withdrawal symptoms. The most common mild withdrawal symptoms were mild sleep disturbance (21/111, 18.9%), mild digestive changes (19/111, 17.1%), and coughing (17/111, 15.3%). Severe withdrawal symptoms were rare, with only 5.4% (6/111) experiencing them. For those achieving 30-day postprogram abstinence, 85% (61/72) had no mild withdrawal symptoms, and 99% (71/72) had no severe withdrawal symptoms. Among successful quitters at day 7, a total of 72.1% (80/111) reported minimal to no cravings, which increased to 88% (63/72) at day 30. Furthermore, 78% (56/72) of those with PA at day 30 reported no change in weight or reduced weight. Among participants experiencing relapse, 48% (28/58) cited intense cravings, 28% (16/58) mentioned facing a tragedy, and 26% (15/58) reported relapsing due to alcohol consumption. The PA rates as a result of the QuitSure program were found to be better than those reported in the results of other smoking-cessation app programs' studies.

CONCLUSIONS

The QuitSure app yields high PA rates and ameliorates symptoms associated with smoking cessation. In order to obtain conclusive evidence regarding the effectiveness and efficacy of the QuitSure program, future research should include appropriate control measures. Nevertheless, the QuitSure program can serve as a valuable adjunct to a conventional smoking cessation treatment program to aid sustained abstinence.

Long-Term Outcomes of a Comprehensive Mobile Smoking Cessation Program With Nicotine Replacement Therapy in Adult Smokers: Pilot Randomized Controlled Trial

BACKGROUND

Increased smartphone ownership has led to the development of mobile smoking cessation programs. Although the related body of evidence, gathered through the conduct of randomized controlled trials (RCTs), has grown in quality and rigor, there is a need for longer-term data to assess associated smoking cessation durability.

OBJECTIVE

The primary aim was to compare smoking cessation outcomes at 52 weeks in adult smokers randomized to a mobile smoking cessation program, Pivot (intervention), versus QuitGuide (control). The secondary aims included comparison of other smoking-related behaviors, outcomes and participant feedback, and exploratory analyses of baseline factors associated with smoking cessation.

METHODS

In this remote pilot RCT, cigarette smokers in the United States were recruited on the web. Participants were offered 12 weeks of free nicotine replacement therapy (NRT). Data were self-reported via a web-based questionnaire with videoconference biovalidation in participants who reported 7-day point-prevalence abstinence (PPA). Outcomes focused on cessation rates with additional assessment of quit attempts, cigarettes per day (CPD), self-efficacy via the Smoking Abstinence Self-Efficacy Questionnaire, NRT use, and participant feedback. Cessation outcomes included self-reported 7- and 30-day PPA, abstinence from all tobacco products, and continuous abstinence. PPA and continuous abstinence were biovalidated using witnessed breath carbon monoxide samples. Exploratory post hoc regression analyses were performed to identify baseline variables associated with smoking cessation.

RESULTS

Participants comprised 188 smokers (n=94, 50% in the Pivot group and n=94, 50% in the QuitGuide group; mean age 46.4, SD 9.2 years; n=104, 55.3% women; n=128, 68.1% White individuals; mean CPD 17.6, SD 9.0). Several cessation rates were higher in the Pivot group (intention to treat): self-reported continuous abstinence was 20% (19/94) versus 9% (8/94; P=.03) for QuitGuide, biochemically confirmed abstinence was 31% (29/94) versus 18% (17/94; P=.04) for QuitGuide, and biochemically confirmed continuous abstinence was 19% (18/94) versus 9% (8/94; P=.046) for QuitGuide. More Pivot participants (93/94, 99% vs 80/94, 85% in the QuitGuide group; P<.001) placed NRT orders (mean 3.3, SD 2.0 vs 1.8, SD 1.6 for QuitGuide; P<.001). Pivot participants had increased self-efficacy via the Smoking Abstinence Self-Efficacy Questionnaire (mean point increase 3.2, SD 7.8, P<.001 vs 1.0, SD 8.5, P=.26 for QuitGuide). QuitGuide participants made more mean quit attempts (7.0, SD 6.3 for Pivot vs 9.5, SD 7.5 for QuitGuide; P=.01). Among those who did not achieve abstinence, QuitGuide participants reported greater CPD reduction (mean -34.6%, SD 35.5% for Pivot vs -46.1%, SD 32.3% for QuitGuide; P=.04). Among those who reported abstinence, 90% (35/39) of Pivot participants and 90% (26/29) of QuitGuide participants indicated that their cessation program helped them quit.

CONCLUSIONS

This pilot RCT supports the long-term effectiveness of the Pivot mobile smoking cessation program, with abstinence rates durable to 52 weeks.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04955639; https://clinicaltrials.gov/ct2/show/NCT04955639.

A Scoping Review and Meta-analysis of the Use of Remote Biochemical Verification Methods of Smoking Status in Tobacco Research

INTRODUCTION

Increasing digital delivery of smoking cessation interventions has resulted in the need to employ novel strategies for remote biochemical verification.

AIMS AND METHODS

This scoping review and meta-analysis aimed to investigate best practices for remote biochemical verification of smoking status. The scientific literature was searched for studies that reported remotely obtained (not in-person) biochemical confirmation of smoking status (ie, combustible tobacco). A meta-analysis of proportions was conducted to investigate key outcomes, which included rates of returned biological samples and the ratio of biochemically verified to self-reported abstinence rates.

RESULTS

A total of 82 studies were included. The most common samples were expired air (46%) and saliva (40% of studies), the most common biomarkers were carbon monoxide (48%) and cotinine (44%), and the most common verification methods were video confirmation (37%) and mail-in samples for lab analysis (26%). Mean sample return rates determined by random-effects meta-analysis were 70% for smoking cessation intervention studies without contingency management (CM), 77% for CM studies, and 65% for other studies (eg, feasibility and secondary analyses). Among smoking cessation intervention studies without CM, self-reported abstinence rates were 21%, biochemically verified abstinence rates were 10%, and 47% of individuals who self-reported abstinence were also biochemically confirmed as abstinent.

CONCLUSIONS

This scoping review suggests that improvements in sample return rates in remote biochemical verification studies of smoking status are needed. Recommendations for reporting standards are provided that may enhance confidence in the validity of reported abstinence rates in remote studies.

IMPLICATIONS

This scoping review and meta-analysis included studies using remote biochemical verification to determine smoking status. Challenges exist regarding implementation and ensuring high sample return rates. Higher self-reported compared to biochemically verified abstinence rates suggest the possibility that participants in remote studies may be misreporting abstinence or not returning samples for other reasons (eg, participant burden, inconvenience). Remote biochemical confirmation of self-reported smoking abstinence should be included in smoking cessation studies whenever feasible. However, findings should be considered in the context of challenges to sample return rates. Better reporting guidelines for future studies in this area are needed.

Effect of digital health, biomarker feedback and nurse or midwife-led counselling interventions to assist pregnant smokers quit: a systematic review and meta-analysis

OBJECTIVE

To assess the effect of digital health (DH), biomarker feedback (BF) and nurse or midwife-led counselling (NoMC) interventions on abstinence in pregnant smokers during pregnancy and postpartum.

SETTINGS

Any healthcare setting servicing pregnant women, including any country globally.

PARTICIPANTS

Pregnant women of any social, ethnic or geographical background who smoke.

METHODS

We searched Embase, Medline, Web Of Science, Google Scholar, PsychINFO, CINAHL and PubMed between 2007 and November 2021. We included published original intervention studies in English with comparators (usual care or placebo). Two independent assessors screened and abstracted data. We performed a random-effects meta-analysis, assessed risk of bias with the Cochrane Tool and used Grading of Recommendations Assessment, Development and Evaluation to assess the quality of evidence.

RESULTS

We identified 57 studies and included 54 in the meta-analysis. Sixteen studies assessed DH (n=3961), 6 BF (n=1643), 32 NoMC (n=60 251), 1 assessed NoMC with BF (n=1120) and 2 NoMC with DH interventions (n=2107). DH interventions had moderate certainty evidence to achieve continuous abstinence (CA) at late pregnancy (4 studies; 2049 women; RR=1.98, 95% CI 1.08 to 3.64, p=0.03) and low certainty evidence to achieve point prevalence abstinence (PPA) postpartum (5 studies; 2238 women; RR=1.46, 95% CI 1.05 to 2.02, p=0.02). NoMC interventions had moderate certainty evidence to achieve PPA in late pregnancy (15 studies; 16 234 women; RR=1.54, 95% CI 1.16 to 2.06, p<0.01) and low certainty evidence to achieve PPA postpartum (13 studies; 5466 women; RR=1.79, 95% CI 1.14 to 2.83, p=0.01). Both DH and BF interventions did not achieve PPA at late pregnancy, nor NoMC interventions achieve CA postpartum. The certainty was reduced due to risk of bias, heterogeneity, inconsistency and/or imprecision.

CONCLUSION

NoMC interventions can assist pregnant smokers achieve PPA and DH interventions achieve CA in late pregnancy. These interventions may achieve other outcomes.

Effectiveness of Health Coaching in Smoking Cessation and Promoting the Use of Oral Smoking Cessation Drugs in Patients with Type 2 Diabetes: A Randomized Controlled Trial

INTRODUCTION

This study looked into the effectiveness of a 6 month health coaching intervention in smoking cessation and smoking reduction for patients with type 2 diabetes.

METHODS

The study was carried out via a two-armed, double-blind, randomized-controlled trial with 68 participants at a medical center in Taiwan. The intervention group received health coaching for 6 months, while the control group only received usual smoking cessation services; some patients in both groups participated in a pharmacotherapy plan. The health coaching intervention is a patient-centered approach to disease management which focuses on changing their actual behaviors. By targeting on achieving effective adult learning cycles, health coaching aims to help patients to establish new behavior patterns and habits.

RESULTS

In this study, the intervention group had significantly more participants who reduced their level of cigarette smoking by at least 50% than the control group (p = 0.030). Moreover, patients participating in the pharmacotherapy plan in the coaching intervention group had a significant effect on smoking cessation (p = 0.011), but it was insignificant in the control group.

CONCLUSIONS

Health coaching can be an effective approach to assisting patients with type 2 diabetes participating in a pharmacotherapy plan to reduce smoking and may help those who participate in pharmacotherapy plan to quit smoking more effectively. Further studies with higher-quality evidence on the effectiveness of health coaching in smoking cessation and the use of oral smoking cessation drugs in patients with type 2 diabetes are needed.

Outcomes of a Comprehensive Mobile Smoking Cessation Program With Nicotine Replacement Therapy in Adult Smokers: Pilot Randomized Controlled Trial

BACKGROUND

Cigarette smoking remains the leading cause of preventable illness and death, underscoring ongoing need for evidence-based solutions. Pivot, a US Clinical Practice Guideline-based mobile smoking cessation program, comprises a personal carbon monoxide breath sensor; a smartphone app; in-app, text-based human-provided coaching; nicotine replacement therapy; and a moderated web-based community. Promising Pivot cohort studies have established the foundation for comparative assessment.

OBJECTIVE

This study aimed to compare engagement, retention, attitudes toward quitting smoking, smoking behavior, and participant feedback between Pivot and QuitGuide, a US Clinical Practice Guideline-based smoking cessation smartphone app from the National Cancer Institute.

METHODS

In this remote pilot randomized controlled trial, cigarette smokers in the United States were recruited on the web and randomized to Pivot or QuitGuide. Participants were offered 12 weeks of free nicotine replacement therapy. Data were self-reported via weekly web-based questionnaires for 12 weeks and at 26 weeks. Outcomes included engagement and retention, attitudes toward quitting smoking, smoking behavior, and participant feedback. The primary outcome was self-reported app openings at 12 weeks. Cessation outcomes included self-reported 7- and 30-day point prevalence abstinence (PPA), abstinence from all tobacco products, and continuous abstinence at 12 and 26 weeks. PPA and continuous abstinence were biovalidated via breath carbon monoxide samples.

RESULTS

Participants comprised 188 smokers (94 Pivot and 94 QuitGuide): mean age 46.4 (SD 9.2) years, 104 (55.3%) women, 128 (68.1%) White individuals, and mean cigarettes per day 17.6 (SD 9.0). Engagement via mean "total app openings through 12 weeks" (primary outcome) was Pivot, 157.9 (SD 210.6) versus QuitGuide, 86.5 (SD 66.3; P<.001). Self-reported 7-day PPA at 12 and 26 weeks was Pivot, 35% (33/94) versus QuitGuide, 28% (26/94; intention to treat [ITT]: P=.28) and Pivot, 36% (34/94) versus QuitGuide, 27% (25/94; ITT: P=.12), respectively. Self-reported 30-day PPA at 12 and 26 weeks was Pivot, 29% (27/94) versus QuitGuide, 22% (21/94; ITT: P=.32) and Pivot, 32% (30/94) versus QuitGuide, 22% (21/94; ITT: P=.12), respectively. The biovalidated abstinence rate at 12 weeks was Pivot, 29% (27/94) versus QuitGuide, 13% (12/94; ITT: P=.008). Biovalidated continuous abstinence at 26 weeks was Pivot, 21% (20/94) versus QuitGuide, 10% (9/94; ITT: P=.03). Participant feedback, including ease of setup, impact on smoking, and likelihood of program recommendation were favorable for Pivot.

CONCLUSIONS

In this randomized controlled trial comparing the app-based smoking cessation programs Pivot and QuitGuide, Pivot participants had higher engagement and biovalidated cessation rates and more favorable user feedback at 12 and 26 weeks. These findings support Pivot as an effective, durable mobile smoking cessation program.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04955639; https://clinicaltrials.gov/ct2/show/NCT04955639.

Practical Technology for Expanding and Improving Substance Use Disorder Treatment: Telehealth, Remote Monitoring, and Digital Health Interventions

The US opioid crisis and the COVID-19 pandemic have sparked innovation in substance use disorder (SUD) treatment such that telehealth, remote monitoring, and digital health interventions are increasingly feasible and effective. These technologies can increase SUD treatment access and acceptability, even for nontreatment seeking, remote, and underserved populations, and can be used to reduce health disparities. Overall, digital tools will likely overcome many barriers to delivery of evidence-based behavioral treatments such as cognitive behavioral therapy and contingency management, that, along with appropriate medications, constitute the foundation of treatment of SUDs.

Long-Term Effectiveness of a Clinician-Assisted Digital Cognitive Behavioral Therapy Intervention for Smoking Cessation: Secondary Outcomes from a Randomized Controlled Trial

Introduction

This study evaluated the secondary effectiveness outcomes for Quit Genius, a digital clinician-assisted cognitive behavioral therapy (CBT) intervention for smoking cessation.

Methods

Adult smokers (N = 556) were randomly assigned to Quit Genius (n = 277), a digital, clinician-assisted CBT intervention or very brief advice (VBA) to stop smoking, an evidence-based, 30-s intervention designed to facilitate quit attempts, coupled with referral to a cessation service (n = 279). Participants were offered combination nicotine replacement therapy (patches and gum) tailored to individual nicotine dependence. Analyses (n = 530), by intention-to-treat, compared Quit Genius and VBA at 4, 26, and 52 weeks post-quit date (QD). The primary outcome was self-reported 7-day point prevalence abstinence (PPA) at 4 weeks post-QD. Consecutive 7-day point-prevalence abstinence, defined as abstinent at two or more consecutive timepoints, was examined at weeks 26 and 52 to indicate long-term effectiveness. Abstinence was verified using a random sample of participants with carbon monoxide breath testing of <5 parts per million (n = 280).

Results

Self-reported consecutive 7-day PPA at weeks 26 and 52 for Quit Genius was 27.2% and 22.6%, respectively, compared with VBA which was 16.6% and 13.2% (RR = 1.70, 95% CI, 1.22-2.37; p = .003, 26 weeks; RR = 1.71, 95% CI, 1.17–2.50; P = .005, 52 weeks). Biochemically verified abstinence was significantly different at 26- (p = .03) but not 52 weeks (p = .16). Quit Genius participants were more likely to remain abstinent than those who received VBA (RR = 1.71, 95% CI 1.17–2.50; p = .005).

Conclusions

This study provides secondary evidence for the long-term effectiveness of Quit Genius in comparison with VBA. Future trials of digital interventions without clinician support and comparisons with active treatment are needed.

Implications

The long-term effectiveness of clinician-assisted digital smoking cessation interventions has not been well studied. This study established the long-term effectiveness of an extended CBT-based intervention; results may inform implementation of scalable approaches to smoking cessation in the health system.

Analysis of Demographic Characteristics of Users of a Free Tobacco Cessation Smartphone App: Observational Study

Background

Tobacco use continues to be the leading preventable cause of death, disease, and disability in the United States. Since 2000, Washington state has offered free tobacco “quitline” services to help its residents stop using tobacco. In 2015, the state began offering free access to a tobacco cessation smartphone app to absorb excess quitline demand. Since most publicly funded tobacco cessation programs are designed to provide access to populations disproportionately impacted by tobacco use, it is important to consider who these public health interventions reach.

Objective

The aim of this study is to understand who used a free cessation app and the extent to which users represented populations disproportionately impacted by tobacco use.

Methods

This is an observational study of 1280 adult Washington state residents who registered for and activated the cessation app. Demographic data were collected as part of the sign-up process, examined using standard descriptive measures, and assessed against state-level surveillance data for representativeness.

Results

Participants were primarily non-Hispanic White (978/1218, 80.3%), identified as female (780/1236, 63.1%), were between ages 25-54 years (903/1186, 76.1%), had at least some college education (836/1222, 68.4%), and reported a household income under US $50,000 (742/1055, 70.3%). Fewer respondents were from rural counties (359/1220, 29.4%); identified as lesbian, gay, bisexual, pansexual, queer, questioning, or asexual (LGBQA; 153/1222, 12.5%); were uninsured (147/1206, 12.2%); or were currently pregnant, planning pregnancy, or breastfeeding (42/624, 6.7%). However, relative to available state data for tobacco users, there was high representation of women, 35- to 54-year-olds, college graduates, and LGBQA individuals, as well as individuals with low household income, poor mental health, Medicaid insurance, and those residing in rural counties.

Conclusions

A diverse population of tobacco users will use a free cessation app, including some demographic groups disproportionately impacted by tobacco use. With high reach and high efficacy, it is possible to address health disparities associated with tobacco use and dependence treatment among certain underserved and at-risk groups.

An innovation involving self-surveillance and serious gaming to increase smoking quit rate: Protocol for a pilot randomized controlled trial

Smoking is a health hazard. Current smoking cessation measures such as behavioral change counselling by trained professionals, nicotine replacement therapy and medications have limited success. Smoking intensity is assessed using a portable device to measure the smokers’ exhaled breath carbon monoxide (eCO) level. A systematic review suggests the potential of serious gaming to increase smoking quit rate. However, the related studies were unable to explain and determine the effect gamification on smoking cessation.

A handy personalized eCO measurement device linked to a smart-phone applications (app) has been developed (integrated STEADES-2 system). This novel system incorporates app-based video and print learning resources, authentication function and gamification using the eCO data as game element. Trained multidisciplinary healthcare professionals access the STEADES-2 data to monitor smoking status and support smokers via asynchronous virtual coaching. The pilot randomized controlled trial will enroll 20 smokers to use the STEADES-2 system (intervention group) and another 20 to the existing smoking cessation programme (control group) in primary care. The primary feasibility outcomes will include the recruitment response rate, the smokers’ usability of the STEADES-2 system, their self eCO monitoring, frequencies of participation in the serious games and interactions with their virtual coaches. Their smoking literacy, utility and experience of the STEADES-2 system are other outcomes. Smokers in both groups will be compared on their cigarette abstinence as secondary outcome based on eCO levels and urine cotinine test (primary outcomes after 12 weeks).

The results will be disseminated via conferences and publications.