A Randomized Trial of Adjunct mHealth Abstinence Reinforcement With Transdermal Nicotine and Counseling for Smoking Cessation

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

BACKGROUND

Rapid advancements in eHealth and mobile health (mHealth) technologies have driven researchers to design and evaluate numerous technology-based interventions to promote smoking cessation. The evolving nature of cessation interventions emphasizes a strong need for knowledge synthesis.

OBJECTIVE

This systematic review and meta-analysis aimed to summarize recent evidence from randomized controlled trials regarding the effectiveness of eHealth-based smoking cessation interventions in promoting abstinence and assess nonabstinence outcome indicators, such as cigarette consumption and user satisfaction, via narrative synthesis.

METHODS

We searched for studies published in English between 2017 and June 30, 2022, in 4 databases: PubMed (including MEDLINE), PsycINFO, Embase, and Cochrane Library. Two independent reviewers performed study screening, data extraction, and quality assessment based on the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework. We pooled comparable studies based on the population, follow-up time, intervention, and control characteristics. Two researchers performed an independent meta-analysis on smoking abstinence using the Sidik-Jonkman random-effects model and log risk ratio (RR) as the effect measurement. For studies not included in the meta-analysis, the outcomes were narratively synthesized.

RESULTS

A total of 464 studies were identified through an initial database search after removing duplicates. Following screening and full-text assessments, we deemed 39 studies (n=37,341 participants) eligible for this review. Of these, 28 studies were shortlisted for meta-analysis. According to the meta-analysis, SMS or app text messaging can significantly increase both short-term (3 months) abstinence (log RR=0.50, 95% CI 0.25-0.75; I2=0.72%) and long-term (6 months) abstinence (log RR=0.77, 95% CI 0.49-1.04; I2=8.65%), relative to minimal cessation support. The frequency of texting did not significantly influence treatment outcomes. mHealth apps may significantly increase abstinence in the short term (log RR=0.76, 95% CI 0.09-1.42; I2=88.02%) but not in the long term (log RR=0.15, 95% CI -0.18 to 0.48; I2=80.06%), in contrast to less intensive cessation support. In addition, personalized or interactive interventions showed a moderate increase in cessation for both the short term (log RR=0.62, 95% CI 0.30-0.94; I2=66.50%) and long term (log RR=0.28, 95% CI 0.04-0.53; I2=73.42%). In contrast, studies without any personalized or interactive features had no significant impact. Finally, the treatment effect was similar between trials that used biochemically verified or self-reported abstinence. Among studies reporting outcomes besides abstinence (n=20), a total of 11 studies reported significantly improved nonabstinence outcomes in cigarette consumption (3/14, 21%) or user satisfaction (8/19, 42%).

CONCLUSIONS

Our review of 39 randomized controlled trials found that recent eHealth interventions might promote smoking cessation, with mHealth being the dominant approach. Despite their success, the effectiveness of such interventions may diminish with time. The design of more personalized interventions could potentially benefit future studies.

TRIAL REGISTRATION

PROSPERO CRD42022347104; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=347104.

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.

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.

Pilot trial of QuitBet: A digital social game that pays you to stop smoking

Contingency management is an effective treatment for cigarette smoking cessation but feasibility and acceptability concerns have been barriers to implementation. We conducted a pilot test of QuitBet, a commercial, digital (smartphone) social game for smoking cessation during which participants earned financial incentives for abstinence. QuitBet included a social feed for posting messages and entirely participant-funded incentives in the form of a deposit contract (the "bet"). QuitBet had a bet of $30 and lasted for 28 days. After a week to prepare for quitting, the quit day was Day 8. Between Day 9-28 (a 20-day period), participants earned back $1 of their $30 bet for each day of carbon monoxide (CO)-verified abstinence (≤ 6 ppm). Remaining bet money was pooled into a "grand prize" pot. Participants who were abstinent on at least 19 of the 20 days (1 "lapse" day allowed) were declared "winners" and split the grand prize pot equally. A game host posted a daily message containing evidence-based education about smoking cessation or a discussion topic. Recruitment goals were met. Among the players (N = 50 U.S. adults, 78% female), 17 (34%) were winners. Thirty-seven participants (74%) responded to a post-QuitBet survey, of whom 95% said they would be interested in playing another QuitBet and would recommend QuitBet to others. Overall, feedback was positive with some suggestions for improvement. In conclusion, a digital social game for smoking cessation with a deposit contract was feasible and acceptable. Next steps include conducting a randomized trial to establish efficacy and a sustainable business model. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Remotely delivered incentives to promote buprenorphine treatment engagement in out-of-treatment adults with opioid use disorder

BACKGROUND

Opioid overdose remains a leading cause of death. Office-based buprenorphine could expand access to treatment to the many opioid users who are not in treatment and who are at risk for opioid overdose. However, many people in need of buprenorphine treatment do not enroll in treatment. This randomized pilot trial evaluated efficacy of a remotely delivered incentive intervention in promoting engagement in buprenorphine treatment in out-of-treatment adults with opioid use disorder.

METHODS

Participants (N = 41) were offered referrals to buprenorphine treatment and randomly assigned to Control or Incentive groups for 6 months. Incentive participants were offered incentives for enrolling in buprenorphine treatment, verified by providing documentation showing that they received a buprenorphine prescription, and providing videos taking daily buprenorphine doses. Participants used a smartphone application to record and submit a video of their buprenorphine prescription and daily buprenorphine administration. Incentive earnings were added remotely to reloadable credit cards.

RESULTS

Incentive participants were significantly more likely to enroll in treatment compared to control participants (71.4 % versus 30.0 % of participants; OR [95 % CI]: 6.24 [1.46-26.72], p = .014). Few participants in either group adhered to buprenorphine treatment, and the two groups continued to use opioids, including fentanyl at high and comparable rates. The two groups did not differ in the percentage of urine samples that were positive for buprenorphine, opiates, fentanyl, or methadone at monthly assessments conducted during the 6-month intervention.

CONCLUSIONS

Remotely delivered incentives can connect out-of-treatment adults with opioid use disorder to treatment, but additional supports are needed to promote buprenorphine adherence.

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

Mobile telephone-delivered contingency management interventions promoting behaviour change in individuals with substance use disorders: a meta-analysis

BACKGROUND/AIMS

Contingency management (CM) interventions have gained considerable interest due to their success in the treatment of addiction. However, their implementation can be resource-intensive for clinical staff. Mobile telephone-based systems might offer a low-cost alternative. This approach could facilitate remote monitoring of behaviour and delivery of the reinforcer and minimize issues of staffing and resources. This systematic review and meta-analysis assessed the evidence for the effectiveness of mobile telephone-delivered CM interventions to promote abstinence (from drugs, alcohol and tobacco), medication adherence and treatment engagement among individuals with substance use disorders.

DESIGN

A systematic search of databases (PsychINFO, CINAHL, MEDLINE PubMed, CENTRAL, Embase) for randomized controlled trials and within-subject design studies (1995-2019). The review was conducted in accordance with the PRISMA statement. The protocol was registered on PROSPERO.

SETTING

All included studies originated in the United states.

PARTICIPANTS

Seven studies were found, including 222 participants; two targeted alcohol abstinence among frequent drinkers and four targeted smoking cessation (in homeless veterans and those with post-traumatic stress disorder). One targeted medication adherence.

MEASURES

The efficacy of CM to increase alcohol and nicotine abstinence was compared with control using several outcomes; percentage of negative samples (PNS), quit rate (QR) and longest duration abstinent (LDA) at the end of the intervention.

FINDINGS

The random-effects meta-analyses produced pooled effect sizes of; PNS [d = 0.94, 95% confidence interval (CI) = 0.63-1.25], LDA (d = 1.08, 95% CI = 0.69-1.46) and QR (d = 0.46, 95% CI = 0.27-0.66), demonstrating better outcomes across the CM conditions. Most of the studies were rated as of moderate quality. 'Fail-safe N' computations for PNS indicated that 50 studies would be needed to produce a non-significant overall effect size. None could be calculated for QR and LDA due to insufficient number of studies.

CONCLUSION

Mobile telephone-delivered contingency management performs significantly better than control conditions in reducing tobacco and alcohol use among adults not in treatment for substance use disorders.

Mobile phone text messaging and app-based interventions for smoking cessation

BACKGROUND

Mobile phone-based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face-to-face support. In addition, mCessation can be automated and therefore provided affordably even in resource-poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.

OBJECTIVES

To determine whether mobile phone-based smoking cessation interventions increase smoking cessation rates in people who smoke.

SEARCH METHODS

For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.

SELECTION CRITERIA

Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone-based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six-month follow-up.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta-analyses of the most stringent measures of abstinence at six months' follow-up or longer, using a Mantel-Haenszel random-effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.

MAIN RESULTS

This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high-income countries. There was moderate-certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I² = 71%; 13 studies, 14,133 participants). There was also moderate-certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I² = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high- and low-intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I² = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I² = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower-intensity smoking cessation support (either a lower-intensity app or non-app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I² = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that automated text message-based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate-certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.

Technology-Based Contingency Management in the Treatment of Substance-Use Disorders

Contingency management is one of the most efficacious interventions to promote drug abstinence. Contingency management has traditionally been delivered in person so that clinicians could confirm drug abstinence and provide access to additional therapeutic services. Now, new technologies not only permit remote confirmation of abstinence, but also remote delivery of incentives. We discuss several technology-based tools to assess substance use, and new ways to deliver contingency management to promote tobacco, alcohol, and cannabis abstinence. These new tools have the potential to dramatically increase access while maintaining high levels of treatment fidelity. Technology-based methods also allow arranging group contingencies that harness online communities, and they permit targeting multiple health-risk behaviors with a combination of sensor-based technologies. Overall, there are unprecedented opportunities to link technology with contingency management to promote drug abstinence.

Contingency management and cognitive behavioral therapy for trauma-exposed smokers with and without posttraumatic stress disorder

INTRODUCTION

Trauma-exposed individuals with and without posttraumatic stress disorder (PTSD) are more likely to smoke and less successful in quit attempts than individuals without psychopathology. Contingency management (CM) techniques (i.e., incentives for abstinence) have demonstrable efficacy for smoking cessation in some populations with psychopathology, but have not been well tested in PTSD. This pilot study examined the feasibility of CM plus brief cognitive behavioral therapy (CBT) in promoting smoking cessation among trauma-exposed individuals with and without PTSD.

METHODS

Fifty trauma-exposed smokers (18 with PTSD) were asked to abstain from tobacco and nicotine replacement therapy for one month. During week one of cessation, CBT was provided daily and increasing CM stipends were paid for each continuous day of biochemically-verified abstinence; CM stipends were withheld in response to smoking lapses and reset to the initial payment level upon abstinence resumption. CBT and fixed payments for study visits were provided during the subsequent three weeks.

RESULTS

Of the 50 eligible participants who attended at least one pre-quit visit (49% female, 35% current PTSD), 43 (86%) attended the first post-quit study visit, 32 (64%) completed the first week of CM/CBT treatment, and 26 (52%) completed the study. Post-quit seven-day point prevalence abstinence rates for participants with and without PTSD, respectively, were similar: 39% vs. 38% (1 week), 33% vs. 28% (2 weeks), 22% vs. 19% (3 weeks), and 22% vs. 13% (4 weeks).

CONCLUSIONS

Use of CM + CBT to support tobacco abstinence is a promising intervention for trauma-exposed smokers with and without PTSD.

Competitions for smoking cessation

BACKGROUND

Competitions might encourage people to undertake and/or reinforce behaviour change, including smoking cessation. Competitions involve individuals or groups having the opportunity to win a prize following successful cessation, either through direct competition or by entry into a lottery or raffle.

OBJECTIVES

To determine whether competitions lead to higher long-term smoking quit rates. We also aimed to examine the impact on the population, the costs, and the unintended consequences of smoking cessation competitions.

SEARCH METHODS

This review has merged two previous Cochrane reviews. Here we include studies testing competitions from the reviews 'Competitions and incentives for smoking cessation' and 'Quit & Win interventions for smoking cessation'. We updated the evidence by searching the Cochrane Tobacco Addiction Group Specialized Register in June 2018.

SELECTION CRITERIA

We considered randomized controlled trials (RCTs), allocating individuals, workplaces, groups within workplaces, or communities to experimental or control conditions. We also considered controlled studies with baseline and post-intervention measures in which participants were assigned to interventions by the investigators. Participants were smokers, of any age and gender, in any setting. Eligible interventions were contests, competitions, lotteries, and raffles, to reward cessation and continuous abstinence in smoking cessation programmes.

DATA COLLECTION AND ANALYSIS

For this update, data from new studies were extracted independently by two review authors. The primary outcome measure was abstinence from smoking at least six months from the start of the intervention. We performed meta-analyses to pool study effects where suitable data were available and where the effect of the competition component could be separated from that of other intervention components, and report other findings narratively.

MAIN RESULTS

Twenty studies met our inclusion criteria. Five investigated performance-based reward, where groups of smokers competed against each other to win a prize (N = 915). The remaining 15 used performance-based eligibility, where cessation resulted in entry into a prize draw (N = 10,580). Five of these used Quit & Win contests (N = 4282), of which three were population-level interventions. Fourteen studies were RCTs, and the remainder quasi-randomized or controlled trials. Six had suitable abstinence data for a meta-analysis, which did not show evidence of effectiveness of performance-based eligibility interventions (risk ratio (RR) 1.16, 95% confidence interval (CI) 0.77 to 1.74, N = 3201, I2 = 57%). No trials that used performance-based rewards found a beneficial effect of the intervention on long-term quit rates.The three population-level Quit & Win studies found higher smoking cessation rates in the intervention group (4% to 16.9%) than the control group at long-term follow-up, but none were RCTs and all had important between-group differences in baseline characteristics. These studies suggested that fewer than one in 500 smokers would quit because of the contest.Reported unintended consequences in all sets of studies generally related to discrepancies between self-reported smoking status and biochemically-verified smoking status. More serious adverse events were not attributed to the competition intervention.Using the GRADE system we rated the overall quality of the evidence for smoking cessation as 'very low', because of the high and unclear risk of bias associated with the included studies, substantial clinical and methodological heterogeneity, and the limited population investigated.

AUTHORS' CONCLUSIONS

At present, it is impossible to draw any firm conclusions about the effectiveness, or a lack of it, of smoking cessation competitions. This is due to a lack of well-designed comparative studies. Smoking cessation competitions have not been shown to enhance long-term cessation rates. The limited evidence suggesting that population-based Quit & Win contests at local and regional level might deliver quit rates above baseline community rates has not been tested adequately using rigorous study designs. It is also unclear whether the value or frequency of possible cash reward schedules influence the success of competitions. Future studies should be designed to compensate for the substantial biases in the current evidence base.

Which eHealth interventions are most effective for smoking cessation? A systematic review

PURPOSE

To synthesize evidence of the effects and potential effect modifiers of different electronic health (eHealth) interventions to help people quit smoking.

METHODS

Four databases (MEDLINE, PsycINFO, Embase, and The Cochrane Library) were searched in March 2017 using terms that included "smoking cessation", "eHealth/mHealth" and "electronic technology" to find relevant studies. Meta-analysis and meta-regression analyses were performed using Mantel-Haenszel test for fixed-effect risk ratio (RR) and restricted maximum-likelihood technique, respectively. Protocol Registration Number: CRD42017072560.

RESULTS

The review included 108 studies and 110,372 participants. Compared to nonactive control groups (eg, usual care), smoking cessation interventions using web-based and mobile health (mHealth) platform resulted in significantly greater smoking abstinence, RR 2.03 (95% CI 1.7-2.03), and RR 1.71 (95% CI 1.35-2.16), respectively. Similarly, smoking cessation trials using tailored text messages (RR 1.80, 95% CI 1.54-2.10) and web-based information and conjunctive nicotine replacement therapy (RR 1.29, 95% CI 1.17-1.43) may also increase cessation. In contrast, little or no benefit for smoking abstinence was found for computer-assisted interventions (RR 1.31, 95% CI 1.11-1.53). The magnitude of effect sizes from mHealth smoking cessation interventions was likely to be greater if the trial was conducted in the USA or Europe and when the intervention included individually tailored text messages. In contrast, high frequency of texts (daily) was less effective than weekly texts.

CONCLUSIONS

There was consistent evidence that web-based and mHealth smoking cessation interventions may increase abstinence moderately. Methodologic quality of trials and the intervention characteristics (tailored vs untailored) are critical effect modifiers among eHealth smoking cessation interventions, especially for web-based and text messaging trials. Future smoking cessation intervention should take advantages of web-based and mHealth engagement to improve prolonged abstinence.

Current, future and potential use of mobile and wearable technologies and social media data in the ABCD study to increase understanding of contributors to child health

Mobile and wearable technologies and novel methods of data collection are innovating health-related research. These technologies and methods allow for multi-system level capture of data across environmental, physiological, behavioral, and psychological domains. In the Adolescent Brain Cognitive Development (ABCD) Study, there is great potential for harnessing the acceptability, accessibility, and functionality of mobile and social technologies for in-vivo data capture to precisely measure factors, and interactions between factors, that contribute to childhood and adolescent neurodevelopment and psychosocial and health outcomes. Here we discuss advances in mobile and wearable technologies and methods of analysis of geospatial, ecologic, social network and behavioral data. Incorporating these technologies into the ABCD study will allow for interdisciplinary research on the effects of place, social interactions, environment, and substance use on health and developmental outcomes in children and adolescents.

Contingency management treatment for substance use disorders: How far has it come, and where does it need to go?

Contingency management (CM) interventions consistently improve substance abuse treatment outcomes, yet CM remains a highly controversial intervention and is rarely implemented in practice settings. This article briefly outlines the evidence base of CM and then describes 4 of the most often-cited concerns about it: philosophical, motivational, durability, and economic. Data supporting and refuting each of these issues are reviewed. The article concludes with suggestions to address these matters and other important areas for CM research and implementation, with the aims of improving uptake of this efficacious intervention in practice settings and outcomes of patients with substance use disorders. (PsycINFO Database Record

Contingency Management: New Directions and Remaining Challenges for An Evidence-Based Intervention

This article introduces the special issue on contingency management (CM), an efficacious intervention for the treatment of substance use disorders with low uptake in clinical settings that is not commensurate with evidence for efficacy. In this special issue of the Journal of Substance Abuse Treatment, we present 16 articles representing the latest research in efficacy, implementation, and technological advances related to CM. Combined, this collection of articles highlights the diverse populations, settings, and applications of CM in the treatment of substance use disorders. We conclude by highlighting directions for future research, particularly those that may increase CM's appeal and uptake in routine clinical care.

Treatment Satisfaction in a Randomized Clinical Trial of mHealth Smoking Abstinence Reinforcement

The importance of patient satisfaction in modern healthcare is widely recognized, but research on satisfaction in the context of smoking cessation has not kept pace. The purpose of this study was to explore treatment satisfaction in a sample of smokers (N=84) randomized to one of two smoking cessation treatment interventions (mHealth reinforcement and mHealth monitoring) that used cell phone-based procedures to monitor smoking status in individuals' natural environments for 4 weeks. Starting on the target quit date, participants received usual care smoking cessation treatment consisting of 8 weeks of transdermal nicotine and 4 weeks of twice-weekly telephone counseling were also prompted 1 to 3 times daily (with exact number and timing not disclosed beforehand) to use a study cell phone and CO monitor to complete a CO self-test, video-record the process, and submit videos using multimedia messaging within 2 hours. mHealth reinforcement participants could earn prizes for smoking-negative on-time CO tests. A treatment satisfaction survey was completed at the end of the 4-week monitoring/reinforcement phase. Results indicate that participants overwhelmingly endorsed high levels of overall satisfaction in both conditions. Treatment adherence did not differ between conditions, but was positively associated with endorsing the highest satisfaction with help quitting with the intervention (p<.01 to .03). mHealth reinforcement was associated with increased longest duration of abstinence (p<.01). Controlling for relevant participant characteristics and treatment adherence, longest duration of abstinence robustly predicted highest satisfaction with help quitting and mediated the effect of treatment condition on that satisfaction. Further research on treatment satisfaction may aid the development of effective abstinence reinforcement and other smoking cessation interventions.