Smoking cessation via the internet: a randomized clinical trial of an internet intervention as adjuvant treatment in a smoking cessation intervention

CBT4CBT web-based add-on treatment for cocaine use disorder: Study protocol for a randomized controlled trial

Background

Cocaine use disorder (CUD) is a chronic condition that presents high relapse rates and treatment dropouts. Web-based interventions have proven to be effective when optimizing face-to-face treatments in different mental health conditions and have the potential to optimize current CUD treatments. However, web-based interventions in addictive behaviors are still limited. The aim of this study is to evaluate whether adding a web-based cognitive behavioral therapy (i.e., CBT4CBT) to standard CUD treatment, improves treatment outcomes in a Spanish sample of patients with severe CUD (which requires inpatient treatment). Additionally, we aim to explore predictive factors of treatment response and treatment gender-related differences.

Methods

All individuals coming for inpatient cocaine detoxification who meet the inclusion criteria will have the possibility to be part of the study. The participants of this open-label randomized controlled clinical trial (RCT) will be allocated to treatment as usual (TAU) or TAU+CBT4CBT after the hospitalization for cocaine detoxification. During the inpatient treatment they will all receive an individualized psychological intervention. There will be six time point assessments: at 48-72 h of starting inpatient treatment, at the end of inpatient treatment and before starting day care and outpatient treatment, at the end of the 8 weeks CTB4CBT / TAU arm treatment and at three follow-up time points (1-, 3-, and 6-months post-treatment).

Discussion

To the best of our knowledge, this is the first RCT that explores the efficacy of adding a web-based cognitive behavioral therapy to usual CUD treatment with patients of a clinical sample in Europe.

Trial registration

IIBSP-CTB-2020-116, NCT05207228. Submitted 8^th of April 2021, posted 26 ^st of January 2022. https://clinicaltrials.gov/ct2/show/NCT05207228?cond=Cocaine+Use+Disorder&draw=2&rank=1.

Effectiveness of the Internet-Based Versus Face-to-Face Interaction on Reduction of Tobacco Use Among Adults: A Meta-Analysis

Literature reported the effectiveness of internet-based interventions over face-to-face interaction on tobacco quitting; however, limited sample size reinforces to integrate and analyze these studies' findings to reach a single conclusion. Therefore, we evaluated the effectiveness of the internet as an intervention approach versus face-to-face interaction on reducing tobacco use among adults. A systematic search was performed through various electronic databases such as Medline, PsychInfo, PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), ResearchGate, Google Scholar, and Academia. Reference lists of the eligible articles were also screened. Full-text articles were included as per eligibility criteria (PICO framework). No ethnicity restriction was applied. A total of 13 studies were selected for meta-analysis, with 3852 and 3908 participants in intervention and control groups, respectively. Forest plot favours the intervention group at one month follow up for tobacco quitting (OR: 2.37, CI: 1.86-3.02, P=0.00001, I2=0%), at three months (OR: 1.88, CI: 1.48-2.40, P=0.00001, I2=42%) at six months (OR: 2.02, CI: 1.64-2.50, P=0.00001, I2=38%) and at one year of follow-up (OR: 1.43, CI: 1.18-1.74, P=0.00001, I2=36%) comparing to control group. Conclusively, internet and web-based interventions are highly useful in tobacco quitting at one month, three months, six months, and one year of follow-up compared to face-to-face interaction or no intervention, although the level of evidence was moderate. Additionally, limited trials in developing countries, arising need for research on internet use for tobacco control in developing countries.

Smoking Treatment: A Report Card on Progress and Challenges

The impact of tobacco smoking treatment is determined by its reach into the smoking population and the effectiveness of its interventions. This review evaluates the reach and effectiveness of pharmacotherapy and psychosocial interventions for smoking. Historically, the reach of smoking treatment has been low, and therefore its impact has been limited, but new reach strategies such as digital interventions and health care system changes offer great promise. Pharmacotherapy tends to be more effective than psychosocial intervention when used clinically, and newer pharmacotherapy strategies hold great promise of further enhancing effectiveness. However, new approaches are needed to advance psychosocial interventions; progress has stagnated because research and dissemination efforts have focused too narrowly on skill training despite evidence that its core content may be inconsequential and the fact that its mechanisms are either unknown or inconsistent with supporting theory. Identifying effective psychosocial content and its mechanisms of action could greatly enhance the effectiveness of counseling, digital, and web interventions.

NIATx-TI versus typical product training on e-health technology implementation: a clustered randomized controlled trial study protocol

BACKGROUND

Substance use disorders (SUDs) lead to tens-of-thousands of overdose deaths and other forms of preventable deaths in the USA each year. This results in over $500 billion per year in societal and economic costs as well as a considerable amount of grief for loved ones of affected individuals. Despite these health and societal consequences, only a small percentage of people seek treatment for SUDs, and the majority of those that seek help fail to achieve long-term sobriety. E-health applications in healthcare have proven to be effective at sustaining treatment and reaching patients traditional treatment pathways would have missed. However, e-health adoption and sustainment rates in healthcare are poor, especially in the SUD treatment sector. Implementation engineering can address this gap in the e-health field by augmenting existing implementation models, which explain organizational and individual e-health behaviors retrospectively, with prospective resources that can guide implementation.

METHODS

This cluster randomized control trial is designed to test two implementation strategies at adopting an evidence-based mobile e-health technology for SUD treatment. The proposed e-health implementation model is the Network for the Improvement of Addiction Treatment-Technology Implementation (NIATx-TI) Framework. This project, based in Iowa, will compare a control condition (using a typical software product training approach that includes in-person staff training followed by access to on-line support) to software implementation utilizing NIATx-TI, which includes change management training, followed by coaching on how to implement and use the mobile application. While e-health spans many modalities and health disciplines, this project will focus on implementing the Addiction Comprehensive Health Enhancement Support System (A-CHESS), an evidence-based SUD treatment recovery app framework. This trial will be conducted in Iowa at 46 organizational sites within 12 SUD treatment agencies. The control arm consists of 23 individual treatment sites based at five organizations, and the intervention arm consists of 23 individual SUD treatment sites based at seven organizations DISCUSSION: This study addresses an issue of substantial public health significance: enhancing the uptake of the growing inventory of patient-centered evidence-based addiction treatment e-health technologies.

TRIAL REGISTRATION

ClinicalTrials.gov , NCT03954184 . Posted 17 May 2019.

Feasibility of a Smartphone-Based Tobacco Treatment for HIV-Infected Smokers

BACKGROUND

Cigarette smoking is common among persons living with HIV (PLWH) in the United States. It is the leading cause of mortality in this group, and efforts to promote cessation have been largely unsuccessful.

METHODS

From 2015 to 2017, we performed a randomized controlled trial of Positively Smoke Free-Mobile (PSF-M) versus standard care. PSF-M is a mobile Web site that offers a 42-day text message-based quit-smoking program with smartphone features including quit-day selection/calendar, educational/motivational videos, and HELP button for cravings.

RESULTS

One hundred individuals enrolled, 48 were randomized to PSF-M (mean age = 45 years, 54% male, 81% black, 31% Latino) and 52 to the standard care condition. All participants were offered a 3-month supply of nicotine patches. Participants randomized to the mobile intervention visited the PSF-M home page a mean of 83 times, viewed 5.6/8 videos, logged in on 13 of 42 possible days, and received 131 texts. Among them, 77% tapped HELP for cravings, and craving response options were used by the following proportions: phone-a-friend, 58%; play-a-game, 29%; play-a-song, 4%. Older age and nonblack race were both associated with higher levels of engagement with the site. Of participants, 61% rated PSF-M very or extremely helpful, and 98% would recommend PSF-M to PLWH family or friends. Abstinence at 3 months, quit attempts, and daily cigarette intake all favored PSF-M over standard care but did not achieve statistical significance in our pilot sample.

CONCLUSIONS

Smartphone-based tobacco treatment for PLWH was feasible and achieved moderate-high rates of engagement and satisfaction in a middle-aged, ethnic or racial minority group in the poorest urban community in the United States.

IMPLICATIONS

Cigarette smoking has emerged as the leading killer of PLWH. Behavioral interventions have achieved only limited success in promoting cessation in this population. In this study, we explore the feasibility and preliminary efficacy of a multimodal, Web-based, quit-smoking intervention delivered to PLWH smokers via their smartphones.

The Use of Web-Based Support Groups Versus Usual Quit-Smoking Care for Men and Women Aged 21-59 Years: Protocol for a Randomized Controlled Trial

Background

Existing smoking cessation treatments are challenged by low engagement and high relapse rates, suggesting the need for more innovative, accessible, and interactive treatment strategies. Twitter is a Web-based platform that allows people to communicate with each other throughout the day using their phone.

Objective

This study aims to leverage the social media platform of Twitter for fostering peer-to-peer support to decrease relapse with quitting smoking. Furthermore, the study will compare the effects of coed versus women-only groups on women’s success with quitting smoking.

Methods

The study design is a Web-based, three-arm randomized controlled trial with two treatment arms (a coed or women-only Twitter support group) and a control arm. Participants are recruited online and are randomized to one of the conditions. All participants will receive 8 weeks of combination nicotine replacement therapy (patches plus their choice of gum or lozenges), serial emails with links to Smokefree.gov quit guides, and instructions to record their quit date online (and to quit smoking on that date) on a date falling within a week of initiation of the study. Participants randomized to a treatment arm are placed in a fully automated Twitter support group (coed or women-only), paired with a buddy (matched on age, gender, location, and education), and encouraged to communicate with the group and buddy via daily tweeted discussion topics and daily automated feedback texts (a positive tweet if they tweet and an encouraging tweet if they miss tweeting). Recruited online from across the continental United States, the sample consists of 215 male and 745 female current cigarette smokers wanting to quit, aged between 21 and 59 years. Self-assessed follow-up surveys are completed online at 1, 3, and 6 months after the date they selected to quit smoking, with salivary cotinine validation at 3 and 6 months. The primary outcome is sustained biochemically confirmed abstinence at the 6-month follow-up.

Results

From November 2016 to September 2018, 960 participants in 36 groups were recruited for the randomized controlled trial, in addition to 20 participants in an initial pilot group. Data analysis will commence soon for the randomized controlled trial based on data from 896 of the 960 participants (93.3%), with 56 participants lost to follow-up and 8 dropouts.

Conclusions

This study combines the mobile platform of Twitter with a support group for quitting smoking. Findings will inform the efficacy of virtual peer-to-peer support groups for quitting smoking and potentially elucidate gender differences in quit rates found in prior research.

Trial Registration

ClinicalTrials.gov NCT02823028; https://clinicaltrials.gov/ct2/show/NCT02823028

International Registered Report Identifier (IRRID)

DERR1-10.2196/16417

Relapse prevention interventions for smoking cessation

BACKGROUND

A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions have been proposed to help prevent relapse.

OBJECTIVES

To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register, clinicaltrials.gov, and the ICTRP in May 2019 for studies mentioning relapse prevention or maintenance in their title, abstracts, or keywords.

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials of relapse prevention interventions with a minimum follow-up of six months. We included smokers who quit on their own, were undergoing enforced abstinence, or were participating in treatment programmes. We included studies that compared relapse prevention interventions with a no intervention control, or that compared a cessation programme with additional relapse prevention components with a cessation programme alone.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane.

MAIN RESULTS

We included 81 studies (69,094 participants), five of which are new to this update. We judged 22 studies to be at high risk of bias, 53 to be at unclear risk of bias, and six studies to be at low risk of bias. Fifty studies included abstainers, and 30 studies helped people to quit and then tested treatments to prevent relapse. Twenty-eight studies focused on special populations who were abstinent because of pregnancy (19 studies), hospital admission (six studies), or military service (three studies). Most studies used behavioural interventions that tried to teach people skills to cope with the urge to smoke, or followed up with additional support. Some studies tested extended pharmacotherapy. We focused on results from those studies that randomised abstainers, as these are the best test of relapse prevention interventions. Of the 12 analyses we conducted in abstainers, three pharmacotherapy analyses showed benefits of the intervention: extended varenicline in assisted abstainers (2 studies, n = 1297, risk ratio (RR) 1.23, 95% confidence interval (CI) 1.08 to 1.41, I² = 82%; moderate-certainty evidence), rimonabant in assisted abstainers (1 study, RR 1.29, 95% CI 1.08 to 1.55), and nicotine replacement therapy (NRT) in unaided abstainers (2 studies, n = 2261, RR 1.24, 95% Cl 1.04 to 1.47, I² = 56%). The remainder of analyses of pharmacotherapies in abstainers had wide confidence intervals consistent with both no effect and a statistically significant effect in favour of the intervention. These included NRT in hospital inpatients (2 studies, n = 1078, RR 1.23, 95% CI 0.94 to 1.60, I² = 0%), NRT in assisted abstainers (2 studies, n = 553, RR 1.04, 95% CI 0.77 to 1.40, I² = 0%; low-certainty evidence), extended bupropion in assisted abstainers (6 studies, n = 1697, RR 1.15, 95% CI 0.98 to 1.35, I² = 0%; moderate-certainty evidence), and bupropion plus NRT (2 studies, n = 243, RR 1.18, 95% CI 0.75 to 1.87, I² = 66%; low-certainty evidence). Analyses of behavioural interventions in abstainers did not detect an effect. These included studies in abstinent pregnant and postpartum women at the end of pregnancy (8 studies, n = 1523, RR 1.05, 95% CI 0.99 to 1.11, I² = 0%) and at postpartum follow-up (15 studies, n = 4606, RR 1.02, 95% CI 0.94 to 1.09, I² = 3%), studies in hospital inpatients (5 studies, n = 1385, RR 1.10, 95% CI 0.82 to 1.47, I² = 58%), and studies in assisted abstainers (11 studies, n = 5523, RR 0.98, 95% CI 0.87 to 1.11, I² = 52%; moderate-certainty evidence) and unaided abstainers (5 studies, n = 3561, RR 1.06, 95% CI 0.96 to 1.16, I² = 1%) from the general population.

AUTHORS' CONCLUSIONS

Behavioural interventions that teach people to recognise situations that are high risk for relapse along with strategies to cope with them provided no worthwhile benefit in preventing relapse in assisted abstainers, although unexplained statistical heterogeneity means we are only moderately certain of this. In people who have successfully quit smoking using pharmacotherapy, there were mixed results regarding extending pharmacotherapy for longer than is standard. Extended treatment with varenicline helped to prevent relapse; evidence for the effect estimate was of moderate certainty, limited by unexplained statistical heterogeneity. Moderate-certainty evidence, limited by imprecision, did not detect a benefit from extended treatment with bupropion, though confidence intervals mean we could not rule out a clinically important benefit at this stage. Low-certainty evidence, limited by imprecision, did not show a benefit of extended treatment with nicotine replacement therapy in preventing relapse in assisted abstainers. More research is needed in this area, especially as the evidence for extended nicotine replacement therapy in unassisted abstainers did suggest a benefit.

Outcomes and Device Usage for Fully Automated Internet Interventions Designed for a Smartphone or Personal Computer: The MobileQuit Smoking Cessation Randomized Controlled Trial

Background

Many best practice smoking cessation programs use fully automated internet interventions designed for nonmobile personal computers (desktop computers, laptops, and tablets). A relatively small number of smoking cessation interventions have been designed specifically for mobile devices such as smartphones.

Objective

This study examined the efficacy and usage patterns of two internet-based best practices smoking cessation interventions.

Methods

Overall, 1271 smokers who wanted to quit were randomly assigned to (1) MobileQuit (designed for—and constrained its use to—mobile devices, included text messaging, and embodied tunnel information architecture) or (2) QuitOnline (designed for nonmobile desktop or tablet computers, did not include text messages, and used a flexible hybrid matrix-hierarchical information architecture). Primary outcomes included self-reported 7-day point-prevalence smoking abstinence at 3- and 6-month follow-up assessments. Program visits were unobtrusively assessed (frequency, duration, and device used for access).

Results

Significantly more MobileQuit participants than QuitOnline participants reported quitting smoking. Abstinence rates using intention-to-treat analysis were 20.7% (131/633) vs 11.4% (73/638) at 3 months, 24.6% (156/633) vs 19.3% (123/638) at 6 months, and 15.8% (100/633) vs 8.8% (56/638) for both 3 and 6 months. Using Complete Cases, MobileQuit’s advantage was significant at 3 months (45.6% [131/287] vs 28.4% [73/257]) and the combined 3 and 6 months (40.5% [100/247] vs 25.9% [56/216]) but not at 6 months (43.5% [156/359] vs 34.4% [123/329]). Participants in both conditions reported their program was usable and helpful. MobileQuit participants visited their program 5 times more frequently than did QuitOnline participants. Consistent with the MobileQuit’s built-in constraint, 89.46% (8820/9859) of its visits were made on an intended mobile device, whereas 47.72% (691/1448) of visits to QuitOnline used an intended nonmobile device. Among MobileQuit participants, 76.0% (459/604) used only an intended mobile device, 23.0% (139/604) used both mobile and nonmobile devices, and 0.1% (6/604) used only a nonmobile device. Among QuitOnline participants, 31.3% (137/438) used only the intended nonmobile devices, 16.7% (73/438) used both mobile and nonmobile devices, and 52.1% (228/438) used only mobile devices (primarily smartphones).

Conclusions

This study provides evidence for optimizing intervention design for smartphones over a usual care internet approach in which interventions are designed primarily for use on nonmobile devices such as desktop computers, laptops. or tablets. We propose that future internet interventions should be designed for use on all of the devices (multiple screens) that users prefer. We forecast that the approach of designing internet interventions for mobile vs nonmobile devices will be replaced by internet interventions that use a single Web app designed to be responsive (adapt to different screen sizes and operating systems), share user data across devices, embody a pervasive information architecture, and complemented by text message notifications.

Trial Registration

ClinicalTrials.gov NCT01952236; https://clinicaltrials.gov/ct2/show/NCT01952236 (Archived by WebCite at http://www.webcitation.org/6zdSxqbf8)

Additional behavioural support as an adjunct to pharmacotherapy for smoking cessation

BACKGROUND

Pharmacotherapies for smoking cessation increase the likelihood of achieving abstinence in a quit attempt. It is plausible that providing support, or, if support is offered, offering more intensive support or support including particular components may increase abstinence further.

OBJECTIVES

To evaluate the effect of adding or increasing the intensity of behavioural support for people using smoking cessation medications, and to assess whether there are different effects depending on the type of pharmacotherapy, or the amount of support in each condition. We also looked at studies which directly compare behavioural interventions matched for contact time, where pharmacotherapy is provided to both groups (e.g. tests of different components or approaches to behavioural support as an adjunct to pharmacotherapy).

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, clinicaltrials.gov, and the ICTRP in June 2018 for records with any mention of pharmacotherapy, including any type of nicotine replacement therapy (NRT), bupropion, nortriptyline or varenicline, that evaluated the addition of personal support or compared two or more intensities of behavioural support.

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount or type of behavioural support. The intervention condition had to involve person-to-person contact (defined as face-to-face or telephone). The control condition could receive less intensive personal contact, a different type of personal contact, written information, or no behavioural support at all. We excluded trials recruiting only pregnant women and trials which did not set out to assess smoking cessation at six months or longer.

DATA COLLECTION AND ANALYSIS

For this update, screening and data extraction followed standard Cochrane methods. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates, if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a random-effects model.

MAIN RESULTS

Eighty-three studies, 36 of which were new to this update, met the inclusion criteria, representing 29,536 participants. Overall, we judged 16 studies to be at low risk of bias and 21 studies to be at high risk of bias. All other studies were judged to be at unclear risk of bias. Results were not sensitive to the exclusion of studies at high risk of bias. We pooled all studies comparing more versus less support in the main analysis. Findings demonstrated a benefit of behavioural support in addition to pharmacotherapy. When all studies of additional behavioural therapy were pooled, there was evidence of a statistically significant benefit from additional support (RR 1.15, 95% CI 1.08 to 1.22, I² = 8%, 65 studies, n = 23,331) for abstinence at longest follow-up, and this effect was not different when we compared subgroups by type of pharmacotherapy or intensity of contact. This effect was similar in the subgroup of eight studies in which the control group received no behavioural support (RR 1.20, 95% CI 1.02 to 1.43, I² = 20%, n = 4,018). Seventeen studies compared interventions matched for contact time but that differed in terms of the behavioural components or approaches employed. Of the 15 comparisons, all had small numbers of participants and events. Only one detected a statistically significant effect, favouring a health education approach (which the authors described as standard counselling containing information and advice) over motivational interviewing approach (RR 0.56, 95% CI 0.33 to 0.94, n = 378).

AUTHORS' CONCLUSIONS

There is high-certainty evidence that providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking increases quit rates. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 20%, based on a pooled estimate from 65 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support. More research is needed to assess the effectiveness of specific components that comprise behavioural support.

Relapse prevention interventions for smoking cessation

BACKGROUND

A number of treatments can help smokers make a successful quit attempt, but many initially successful quitters relapse over time. Several interventions have been proposed to help prevent relapse.

OBJECTIVES

To assess whether specific interventions for relapse prevention reduce the proportion of recent quitters who return to smoking.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register, clinicaltrials.gov, and the ICTRP in February 2018 for studies mentioning relapse prevention or maintenance in their title, abstracts, or keywords.

SELECTION CRITERIA

Randomised or quasi-randomised controlled trials of relapse prevention interventions with a minimum follow-up of six months. We included smokers who quit on their own, were undergoing enforced abstinence, or were participating in treatment programmes. We included studies that compared relapse prevention interventions with a no intervention control, or that compared a cessation programme with additional relapse prevention components with a cessation programme alone.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane.

MAIN RESULTS

We included 77 studies (67,285 participants), 15 of which are new to this update. We judged 21 studies to be at high risk of bias, 51 to be at unclear risk of bias, and five studies to be at low risk of bias. Forty-eight studies included abstainers, and 29 studies helped people to quit and then tested treatments to prevent relapse. Twenty-six studies focused on special populations who were abstinent because of pregnancy (18 studies), hospital admission (five studies), or military service (three studies). Most studies used behavioural interventions that tried to teach people skills to cope with the urge to smoke, or followed up with additional support. Some studies tested extended pharmacotherapy.We focused on results from those studies that randomised abstainers, as these are the best test of relapse prevention interventions. Of the 12 analyses we conducted in abstainers, three pharmacotherapy analyses showed benefits of the intervention: extended varenicline in assisted abstainers (2 studies, n = 1297, risk ratio (RR) 1.23, 95% confidence interval (CI) 1.08 to 1.41, I² = 82%; moderate certainty evidence), rimonabant in assisted abstainers (1 study, RR 1.29, 95% CI 1.08 to 1.55), and nicotine replacement therapy (NRT) in unaided abstainers (2 studies, n = 2261, RR 1.24, 95% Cl 1.04 to 1.47, I² = 56%). The remainder of analyses of pharmacotherapies in abstainers had wide confidence intervals consistent with both no effect and a statistically significant effect in favour of the intervention. These included NRT in hospital inpatients (2 studies, n = 1078, RR 1.23, 95% CI 0.94 to 1.60, I² = 0%), NRT in assisted abstainers (2 studies, n = 553, RR 1.04, 95% CI 0.77 to 1.40, I² = 0%; low certainty evidence), extended bupropion in assisted abstainers (6 studies, n = 1697, RR 1.15, 95% CI 0.98 to 1.35, I² = 0%; moderate certainty evidence), and bupropion plus NRT (2 studies, n = 243, RR 1.18, 95% CI 0.75 to 1.87, I² = 66%; low certainty evidence). Analyses of behavioural interventions in abstainers did not detect an effect. These included studies in abstinent pregnant and postpartum women at end of pregnancy (8 studies, n = 1523, RR 1.05, 95% CI 0.99 to 1.11, I² = 0%) and at postpartum follow-up (15 studies, n = 4606, RR 1.02, 95% CI 0.94 to 1.09, I² = 3%), studies in hospital inpatients (4 studies, n = 1300, RR 0.95, 95% CI 0.81 to 1.11, I² = 0%), and studies in assisted abstainers (10 studies, n = 5408, RR 0.99, 95% CI 0.87 to 1.13, I² = 56%; moderate certainty evidence) and unaided abstainers (5 studies, n = 3561, RR 1.06, 95% CI 0.96 to 1.16, I² = 1%) from the general population.

AUTHORS' CONCLUSIONS

Behavioural interventions that teach people to recognise situations that are high risk for relapse along with strategies to cope with them provided no worthwhile benefit in preventing relapse in assisted abstainers, although unexplained statistical heterogeneity means we are only moderately certain of this. In people who have successfully quit smoking using pharmacotherapy, there were mixed results regarding extending pharmacotherapy for longer than is standard. Extended treatment with varenicline helped to prevent relapse; evidence for the effect estimate was of moderate certainty, limited by unexplained statistical heterogeneity. Moderate-certainty evidence, limited by imprecision, did not detect a benefit from extended treatment with bupropion, though confidence intervals mean we could not rule out a clinically important benefit at this stage. Low-certainty evidence, limited by imprecision, did not show a benefit of extended treatment with nicotine replacement therapy in preventing relapse in assisted abstainers. More research is needed in this area, especially as the evidence for extended nicotine replacement therapy in unassisted abstainers did suggest a benefit.

Best Practices and Recommendations for Digital Interventions to Improve Engagement and Adherence in Chronic Illness Sufferers

Abstract. Chronic illnesses cause considerable burden in quality of life, often leading to physical, psychological, and social dysfunctioning of the sufferers and their family. There is a growing need for flexible provision of home-based psychological services to increase reach even for traditionally underserved chronic illness sufferer populations. Digital interventions can fulfill this role and provide a range of psychological services to improve functioning. Despite the potential of digital interventions, concerns remain regarding users’ engagement, as low engagement is associated with low adherence rates, high attrition, and suboptimal exposure to the intervention. Human–computer interaction (e.g., theoretical models of persuasive system design, gamification, tailoring, and supportive accountability) and user characteristics (e.g., gender, age, computer literacy) are the main identified culprits contributing to engagement and adherence difficulties. To date, there have not been any clear and concise recommendations for improved utilization and engagement in digital interventions. This paper provides an overview of user engagement factors and proposes research informed recommendations for engagement and adherence planning in digital intervention development. The recommendations were derived from the literature and consensualized by expert members of the European Federation of Psychology Associations, Psychology and Health Standing Committee, and e-Health Task Force. These recommendations serve as a starting point for researchers and clinicians interested in the digitalized health field and promote effective planning for engagement when developing digital interventions with the potential to maximize adherence and optimal exposure in the treatment of chronic health conditions.

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 Smokers' Preferences for Receiving Cessation Information in a Lung Cancer Screening Setting

The purpose of this study was to identify current smokers' communication format preferences for receiving smoking cessation information in a lung cancer screening setting. A cross-sectional correlational design using survey methodology with 159 screening-eligible current smokers was the method used. Data was dichotomized (digital versus traditional preference) and analyzed using Pearson's chi-squared test, Mann-Whitney U test, and logistic regression. Race was a statistically significant predictor with White participants having four times greater odds of reporting preference for a digital format for receiving smoking cessation information such as social media and/or supportive text messages (OR: 4.06; p = 0.004). Lung cancer screening is a new venue where current long-term smokers can be offered information about smoking cessation while they are engaging in a health-promoting behavior and potentially more likely to contemplate quitting. It is important to consider the communication format preference of current smokers to support cessation uptake. This study is the first to examine communication format preference of current smokers in the context of the lung cancer screening venue. Key differences noted by race support the need for further research examining multiple formats of communication with efforts to maximize options in the cancer screening setting.

Exploring Online Asynchronous Counseling With Tobacco Treatment Specialists in the QUIT-PRIMO and National Dental PBRN HI-QUIT Studies: Who Uses It and What Do They Say?

PURPOSE

To describe the content of messages sent by smokers through asynchronous counseling within a Web-based smoking cessation intervention.

DESIGN

Qualitative.

SETTING

National community-based setting of patients who had been engaged by the medical or dental practices at which they attended or via Google advertisements.

PARTICIPANTS

Adults older than 19 years who were current smokers and interested in quitting. Participants throughout the United States referred to a Web-based cessation intervention by their medical or dental provider or by clicking on a Google advertisement.

METHODS

We conducted a qualitative review of 742 asynchronous counseling messages sent by 270 Web site users. Messages were reviewed, analyzed, and organized into qualitative themes by the investigative team.

RESULTS

The asynchronous counseling feature of the intervention was used most frequently by smokers who were white (87%), female (67%), aged 45 to 54 (32%), and who had at least some college-level education (70%). Qualitative analysis yielded 7 basic themes-Talk about the Process of Quitting, Barriers to Quitting, Reasons to Quit, Quit History, Support and Strategies for Quitting, Quitting with Medication, and Quit Progress. The most common theme was Support and Strategies for Quitting with 255 references among all messages.

CONCLUSION

We found rich communication across the spectrum of the quit process, from persons preparing to quit to those who had successfully quit. Asynchronous smoking cessation counseling provides a promising means of social support for smokers during the quit process.

An Interactive Web-Based Intervention to Achieve Healthy Weight in Young Children

This prospective, randomized, controlled trial for parents of overweight and obese 3- to 7-year-olds was performed to assess the feasibility of a program promoting healthy eating and lifestyle by targeting parents as agents of change. The intervention was composed of 6-in-person group sessions and a customized website over 12 months. The control group received customary care. The primary outcome was feasibility of the intervention to promote healthy behavior change measured by attendance. The secondary outcome was effectiveness assessed by attaining reduced body mass index (BMI) z scores, healthy behavior changes and increased parent self-efficacy. Seventy-three child-parent dyads were enrolled; 14 parents never attended any sessions. Participation in follow-up assessments did not meet the hypothesized level. Ultimate BMI z scores did not differ between control and intervention groups. Parenting skills did not improve in the intervention group. This intervention to achieve healthy lifestyle changes in children via their parents as "change agents" was unsuccessful.

Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review

Background

Incorporating social media features into digital behavior change interventions (DBCIs) has the potential to contribute positively to their success. However, the lack of clear design principles to describe and guide the use of these features in behavioral interventions limits cross-study comparisons of their uses and effects.

Objective

The aim of this study was to provide a systematic review of DBCIs targeting modifiable behavioral risk factors that have included social media features as part of their intervention infrastructure. A taxonomy of social media features is presented to inform the development, description, and evaluation of behavioral interventions.

Methods

Search terms were used in 8 databases to identify DBCIs that incorporated social media features and targeted tobacco smoking, diet and nutrition, physical activities, or alcohol consumption. The screening and review process was performed by 2 independent researchers.

Results

A total of 5264 articles were screened, and 143 articles describing a total of 134 studies were retained for full review. The majority of studies (70%) reported positive outcomes, followed by 28% finding no effects with regard to their respective objectives and hypothesis, and 2% of the studies found that their interventions had negative outcomes. Few studies reported on the association between the inclusion of social media features and intervention effect. A taxonomy of social media features used in behavioral interventions has been presented with 36 social media features organized under 7 high-level categories. The taxonomy has been used to guide the analysis of this review.

Conclusions

Although social media features are commonly included in DBCIs, there is an acute lack of information with respect to their effect on outcomes and a lack of clear guidance to inform the selection process based on the features’ suitability for the different behaviors. The proposed taxonomy along with the set of recommendations included in this review will support future research aimed at isolating and reporting the effects of social media features on DBCIs, cross-study comparisons, and evaluations.

Smoking cessation: Exploration of perceived technology-related information value

This study describes a unique approach to information transfer affecting the perceived value of this information and related impact on smoker behavior. Data were collected via survey, sampling approximately 120 participants. An online survey tool was used for the survey creation, data collection and monitoring. Another online tool was used by participants to create short animation videos as a means of increasing their engagement with information in an experiential fashion. Study findings included that the process experienced by the test group was influential and facilitated participants' change of mind regarding enrollment in a smoking cessation workshop. This was partly attributable to the IKEA effect. The study provides evidence that a change in habits crucial to improve health and enhance positive lifestyle choices can be stimulated through active engagement with artifact creation in a technology-mediated environment.

Effects of a culturally specific tobacco cessation intervention among African American Quitline enrollees: a randomized controlled trial

BACKGROUND

African Americans suffer disproportionately from tobacco-related illness and have more difficulty quitting smoking than other racial/ethnic groups. Previous research indicates that African American treatment-seekers are high utilizers of tobacco quitlines, yet cessation rates via quitlines are lower relative to whites. The goal of the present study is to test the effectiveness of adding a culturally specific, video-based, adjunct to standard quitline care. It is hypothesized that the integration of an evidence-based intervention (Pathways to Freedom: Leading the Way to a Smoke-Free Community©; PTF) into quitline services will increase cessation and treatment engagement compared to control conditions, and that effects will be moderated by sociocultural factors (e.g., culturally specific intervention expectancies, acculturation, and ethnic identity).

METHODS

This study is a 3-arm semi-pragmatic randomized controlled trial (RCT). Participants will be 1050 enrollees in the North Carolina State quitline (QuitlineNC) who self-identify as African American. Usual quitline care includes up to 4 proactive quit coaching calls, website access, and two-weeks of nicotine patch therapy. Eligible study participants will be randomized to receive (1) standard quitline services plus PTF (PTF); (2) quitline services plus a standard tobacco cessation DVD (attention control); or (3) quitline services alone (usual care). Assessments will be conducted at baseline, 3 and 6-months post-enrollment. The primary outcome will be biochemically verified 7 day ppa at 6-months. Generalized linear mixed models (GLMMs) and hierarchical logistic regression will be used to assess the effects of treatment group on cessation outcomes and to test potential moderators.

DISCUSSION

This study will answer questions regarding the implementation and effectiveness of integrating a culturally specific video intervention into a real-world, population-level tobacco intervention. It will also aid our understanding of individual-difference variables that are associated with success. If an incremental benefit is found, this trial will have implications for increasing the responsiveness of tobacco quitlines for African Americans, reducing tobacco cessation disparities, and best practices for improving minority health. In addition, the PTF intervention has the potential for widespread disseminated through quitlines, which are available across the United States.

TRIAL REGISTRATION

Clinicaltrials.gov NCT03064971 . Registered on February 22, 2017.

Share2Quit: Online Social Network Peer Marketing of Tobacco Cessation Systems

Introduction

Although technology-assisted tobacco interventions (TATIs) are effective, they are underused due to recruitment challenges. We tested whether we could successfully recruit smokers to a TATI using peer marketing through a social network (Facebook).

Methods

We recruited smokers on Facebook using online advertisements. These recruited smokers (seeds) and subsequent waves of smokers (peer recruits) were provided the Share2Quit peer recruitment Facebook app and other tools. Smokers were incentivized for up to seven successful peer recruitments and had 30 days to recruit from date of registration. Successful peer recruitment was defined as a peer recruited smoker completing the registration on the TATI following a referral. Our primary questions were (1) whether smokers would recruit other smokers and (2) whether peer recruitment would extend the reach of the intervention to harder-to-reach groups, including those not ready to quit and minority smokers.

Results

Overall, 759 smokers were recruited (seeds: 190; peer recruits: 569). Fifteen percent (n = 117) of smokers successfully recruited their peers (seeds: 24.7%; peer recruits: 7.7%) leading to four recruitment waves. Compared to seeds, peer recruits were less likely to be ready to quit (peer recruits 74.2% vs. seeds 95.1%), more likely to be male (67.1% vs. 32.9%), and more likely to be African American (23.8% vs. 10.8%) (p < .01 for all comparisons).

Conclusions

Peer marketing quadrupled our engaged smokers and enriched the sample with not-ready-to-quit and African American smokers. Peer recruitment is promising, and our study uncovered several important challenges for future research.

Implications

This study demonstrates the successful recruitment of smokers to a TATI using a Facebook-based peer marketing strategy. Smokers on Facebook were willing and able to recruit other smokers to a TATI, yielding a large and diverse population of smokers.

SurvivorCHESS to increase physical activity in colon cancer survivors: can we get them moving?

PURPOSE

This randomized controlled trial evaluated the impact of SurvivorCHESS, an eHealth intervention, on physical activity in colon cancer survivors and to explore the impact of SurvivorCHESS on quality of life and distress.

METHODS

This was a two-arm single-blinded multi-site randomized controlled trial comparing a control group to an intervention group receiving a smartphone with the SurvivorCHESS program.

RESULTS

Participants using SurvivorCHESS (n = 144) increased their moderate to vigorous physical activities from 19.4 min at baseline to 50 min compared to the control group (n = 140) increasing from 15.5 to 40.3 min at 6 months (p = .083) but was not sustained 3 months after the study ended. No significant differences were found between groups over time for quality of life or distress items. Reports of physical symptoms were greater than other categories for distress items. Patients who had a higher body mass index and number of comorbid conditions were less likely to increase their physical activity. Self-determination theory including autonomous motivation and relatedness was not associated with the outcomes.

CONCLUSIONS

Physical activity did increase over time in both groups and was not significantly different with the use of the eHealth intervention, SurvivorCHESS, compared to the control group. The amount of SurvivorCHESS use was not associated with physical activity.

IMPLICATIONS FOR CANCER SURVIVORS

Increasing physical activity in colon cancer survivors has the potential to improve quality of life and reduce recurrences. Using smartphone-tracking devices may be useful in helping to change this health behavior.

Internet-based interventions for smoking cessation

BACKGROUND

Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide, making the Internet a potential platform to help people quit smoking.

OBJECTIVES

To determine the effectiveness of Internet-based interventions for smoking cessation, whether intervention effectiveness is altered by tailoring or interactive features, and if there is a difference in effectiveness between adolescents, young adults, and adults.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, which included searches of MEDLINE, Embase and PsycINFO (through OVID). There were no restrictions placed on language, publication status or publication date. The most recent search was conducted in August 2016.

SELECTION CRITERIA

We included randomised controlled trials (RCTs). Participants were people who smoked, with no exclusions based on age, gender, ethnicity, language or health status. Any type of Internet intervention was eligible. The comparison condition could be a no-intervention control, a different Internet intervention, or a non-Internet intervention. To be included, studies must have measured smoking cessation at four weeks or longer.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed and extracted data. We extracted and, where appropriate, pooled smoking cessation outcomes of six-month follow-up or more, reporting short-term outcomes narratively where longer-term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI).We grouped studies according to whether they (1) compared an Internet intervention with a non-active control arm (e.g. printed self-help guides), (2) compared an Internet intervention with an active control arm (e.g. face-to-face counselling), (3) evaluated the addition of behavioural support to an Internet programme, or (4) compared one Internet intervention with another. Where appropriate we grouped studies by age.

MAIN RESULTS

We identified 67 RCTs, including data from over 110,000 participants. We pooled data from 35,969 participants.There were only four RCTs conducted in adolescence or young adults that were eligible for meta-analysis.Results for trials in adults: Eight trials compared a tailored and interactive Internet intervention to a non-active control. Pooled results demonstrated an effect in favour of the intervention (RR 1.15, 95% CI 1.01 to 1.30, n = 6786). However, statistical heterogeneity was high (I² = 58%) and was unexplained, and the overall quality of evidence was low according to GRADE. Five trials compared an Internet intervention to an active control. The pooled effect estimate favoured the control group, but crossed the null (RR 0.92, 95% CI 0.78 to 1.09, n = 3806, I² = 0%); GRADE quality rating was moderate. Five studies evaluated an Internet programme plus behavioural support compared to a non-active control (n = 2334). Pooled, these studies indicated a positive effect of the intervention (RR 1.69, 95% CI 1.30 to 2.18). Although statistical heterogeneity was substantial (I² = 60%) and was unexplained, the GRADE rating was moderate. Four studies evaluated the Internet plus behavioural support compared to active control. None of the studies detected a difference between trial arms (RR 1.00, 95% CI 0.84 to 1.18, n = 2769, I² = 0%); GRADE rating was moderate. Seven studies compared an interactive or tailored Internet intervention, or both, to an Internet intervention that was not tailored/interactive. Pooled results favoured the interactive or tailored programme, but the estimate crossed the null (RR 1.10, 95% CI 0.99 to 1.22, n = 14,623, I² = 0%); GRADE rating was moderate. Three studies compared tailored with non-tailored Internet-based messages, compared to non-tailored messages. The tailored messages produced higher cessation rates compared to control, but the estimate was not precise (RR 1.17, 95% CI 0.97 to 1.41, n = 4040), and there was evidence of unexplained substantial statistical heterogeneity (I² = 57%); GRADE rating was low.Results should be interpreted with caution as we judged some of the included studies to be at high risk of bias.

AUTHORS' CONCLUSIONS

The evidence from trials in adults suggests that interactive and tailored Internet-based interventions with or without additional behavioural support are moderately more effective than non-active controls at six months or longer, but there was no evidence that these interventions were better than other active smoking treatments. However some of the studies were at high risk of bias, and there was evidence of substantial statistical heterogeneity. Treatment effectiveness in younger people is unknown.

A prospective examination of online social network dynamics and smoking cessation

Introduction

Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual’s number of social network ties are prospectively related to abstinence in an online social network for cessation. In a network where quitting is normative and is the focus of communications among members, we predicted that an increasing number of ties would be positively associated with abstinence.

Method

Participants were N = 2,657 adult smokers recruited to a randomized cessation treatment trial following enrollment on BecomeAnEX.org, a longstanding Internet cessation program with a large and mature online social network. At 3-months post-randomization, 30-day point prevalence abstinence was assessed and website engagement metrics were extracted. The social network was constructed with clickstream data to capture the flow of information among members. Two network centrality metrics were calculated at weekly intervals over 3 months: 1) in-degree, defined as the number of members whose posts a participant read; and 2) out-degree-aware, defined as the number of members who read a participant’s post and commented, which was subsequently viewed by the participant. Three groups of users were identified based on social network engagement patterns: non-users (N = 1,362), passive users (N = 812), and active users (N = 483). Logistic regression modeled 3-month abstinence by group as a function of baseline variables, website utilization, and network centrality metrics.

Results

Abstinence rates varied by group (non-users = 7.7%, passive users = 10.7%, active users = 20.7%). Significant baseline predictors of abstinence were age, nicotine dependence, confidence to quit, and smoking temptations in social situations among passive users (ps < .05); age and confidence to quit among active users. Among centrality metrics, positive associations with abstinence were observed for in-degree increases from Week 2 to Week 12 among passive and active users, and for out-degree-aware increases from Week 2 to Week 12 among active users (ps < .05).

Conclusions

This study is the first to demonstrate that increased tie formation among members of an online social network for smoking cessation is prospectively associated with abstinence. It also highlights the value of using individuals’ activities in online social networks to predict their offline health behaviors.

Improving Adherence to Smoking Cessation Treatment: Intervention Effects in a Web-Based Randomized Trial

BACKGROUND

Web-based smoking cessation interventions can deliver evidence-based treatments to a wide swath of the population, but effectiveness is often limited by insufficient adherence to proven treatment components. This study evaluated the impact of a social network (SN) intervention and free nicotine replacement therapy (NRT) on adherence to evidence-based components of smoking cessation treatment in the context of a Web-based intervention.

METHODS

A sample of adult U.S. smokers (N = 5290) was recruited via BecomeAnEX.org, a free smoking cessation Web site. Smokers were randomized to one of four arms: (1) an interactive, evidence-based smoking cessation Web site (WEB) alone; (2) WEB in conjunction with an SN intervention designed to integrate participants into the online community (WEB+SN); (3) WEB plus free NRT (WEB+NRT); and (4) the combination of all treatments (WEB+SN+NRT). Adherence outcomes assessed at 3-month follow-up were as follows: Web site utilization metrics, use of skills training components, intratreatment social support, and pharmacotherapy use.

RESULTS

WEB+SN+NRT outperformed all others on Web site utilization metrics, use of practical counseling tools, intratreatment social support, and NRT use. It was the only intervention to promote the sending of private messages and the viewing of community pages over WEB alone. Both social network arms outperformed WEB on most metrics of online community engagement. Both NRT arms showed higher medication use compared to WEB alone.

CONCLUSIONS

This study demonstrated the effectiveness of two approaches for improving adherence to evidence-based components of smoking cessation treatment. Integrated approaches to medication provision and social network engagement can enhance adherence to components known to improve cessation.

IMPLICATIONS

This study demonstrated that an integrated approach to medication provision and social network integration, when delivered through an online program, can enhance adherence across all three recommended components of an evidence-based smoking cessation program (skills training, social support, and pharmacotherapy use). Nicotine replacement therapy-when provided as part of an integrated program-increases adherence to other program elements, which in turn augment its own therapeutic effects. An explicit focus on approaches to improve treatment adherence is an important first step to identifying leverage points for optimizing intervention effectiveness.

Social Networks Across Common Cancer Types: The Evidence, Gaps, and Areas of Potential Impact

Although the association between social context and health has been demonstrated previously, much less is known about network interactions by gender, race/ethnicity, and sociodemographic characteristics. Given the variability in cancer outcomes among groups, research on these relationships may have important implications for addressing cancer health disparities. We examined the literature on social networks and cancer across the cancer continuum among adults. Relevant studies (N=16) were identified using two common databases: PubMed and Google Scholar. Most studies used a prospective cohort study design (n=9), included women only (n=11), and were located in the United States (n=14). Seventy-five percent of the studies reviewed used a validated scale or validated items to measure social networks (n=12). Only one study examined social network differences by race, 57.1% (n=8) focused on breast cancer alone, 14.3% (n=2) explored colorectal cancer or multiple cancers simultaneously, and 7.1% (n=1) only prostate cancer. More than half of the studies included multiple ethnicities in the sample, while one study included only low-income subjects. Despite findings of associations between social networks and cancer survival, risk, and screening, none of the studies utilized social networks as a mechanism for reducing health disparities; however, such an approach has been utilized for infectious disease control. Social networks and the support provided within these networks have important implications for health behaviors and ultimately cancer disparities. This review serves as the first step toward dialog on social networks as a missing component in the social determinants of cancer disparities literature that could move the needle upstream to target adverse cancer outcomes among vulnerable populations.

Online tobacco websites and online communities-who uses them and do users quit smoking? The quit-primo and national dental practice-based research network Hi-Quit studies

Online tobacco cessation communities are beneficial but underused. Our study examined whether, among smokers participating in a web-assisted tobacco intervention (Decide2quit.org), specific characteristics were associated with navigating to BecomeAnEx.org, an online cessation community, and with subsequent quit rates. Among smokers (N = 759) registered with Decide2quit.org, we identified visitors to BecomeAnEx.org, examining associations between smoker characteristics and likelihood of visiting. We then tested for associations between visits and 6-month cessation (point prevalence). We also tested for an interaction between use of other online support-seeking (Decide2quit.org tobacco cessation coaches), visiting, and 6-month cessation. One quarter (26.0 %; n = 197) of the smokers visited BecomeAnEx.org; less than one tenth (7.5 %; n = 57) registered to participate in the online forum. Visitors were more likely to be female (73.0 vs. 62.6 % of non-visitors, P < 0.01) to have visited a cessation website before (33.0 vs. 17.4 %, P < 0.01) and to report quit attempts in the previous year (62.0 vs. 53.0 %, P = 0.03). In analyses of all participants, BecomeAnEx.org visiting was not associated with 6-month quit completion. Among participants who communicated with a coach, BecomeAnEx.org visiting also lacked a significant association with 6 month quit completion, although a non-significant trend toward quit completion in visitors was noted (OR 2.21, 95 % CI 0.81-3.1). Online cessation communities attract smokers with previous cessation website experience and recent quit attempts. Community visiting was not associated with quit rates in our study, but low use may have limited our power to detect differences. Further research should explore whether an additive effect can be achieved by offering community visitors support via online coaches.

Get with the program: Adherence to a smartphone app for smoking cessation

INTRODUCTION

Although engagement is generally predictive of positive outcomes in technology-based behavioral change interventions, engagement measures remain largely atheoretical and lack treatment-specificity. This study examines the extent to which adherence measures based on the underlying behavioral change theory of an Acceptance and Commitment Therapy (ACT) app for smoking cessation predict smoking outcomes, and user characteristics associated with adherence.

METHODS

Study sample was adult daily smokers in a single arm pilot study (n=84). Using the app's log file data, we examined measures of adherence to four key components of the ACT behavior change model as predictors of smoking cessation and reduction. We also examined baseline user characteristics associated with adherence measures that predict smoking cessation.

RESULTS

Fully adherent users (24%) were over four times more likely to quit smoking (OR=4.45; 95% CI=1.13, 17.45; p=0.032). Both an increase in tracking the number of urges passed (OR=1.02; 95% CI=1.00, 1.03; p=0.043) and ACT modules completed (OR=1.27; 95% CI=1.01, 1.60; p=0.042) predicted cessation. Lower baseline acceptance of cravings was associated with over four times higher odds of full adherence (OR=4.59; 95% CI=1.35, 15.54; p=0.014).

CONCLUSIONS

Full adherence and use of specific ACT theory-based components of the app predicted quitting. Consistent with ACT theory, users with low acceptance were most likely to adhere to the app. Further research is needed on ways to promote app engagement.

Web-Based Intervention for Transitioning Smokers From Inpatient to Outpatient Care: An RCT

INTRODUCTION

Smoking-cessation follow-up care after hospitalization is known to be effective. Cost-effective and disseminable interventions adoptable by hospitals are needed.

DESIGN

RCT.

SETTING/PARTICIPANTS

Fourteen hundred eighty-eight current smokers recruited during a tertiary care hospital stay were randomly assigned to Usual Care (UC) or Usual Care plus Web-Based Intervention (WI). Data were collected in 2011-2013 and analyzed in 2014-2015.

INTERVENTION

UC provided brief bedside advice to quit, a quit plan template, and quitline contact information. WI included access to a website with asynchronous e-message communication with a tobacco counselor, use of interactive self-assessments, helpful cessation information, and access to additional web resources, as well as automated e-mail messages tailored for health concern and readiness to quit.

MAIN OUTCOME MEASURES

Self-reported 30-day abstinence at 6 months was the primary outcome; a subset was verified by saliva cotinine.

RESULTS

Six-month follow-up was completed by 83% of participants. No difference was found between study arms for self-reported abstinence rates in intent-to-treat (25.4% WI vs 26.8% UC) and complete case (31.3% WI vs 31.4% UC) analyses. Reduced smoking was reported by 45.5% (WI, n=276) and 47% (UC, n=296) of non-abstinent responders (p=0.59). Using a 10-ng/mL cotinine cut off, abstinence was verified in 52.1% of WI and 62.5% of UC (p=0.11). Significant covariates associated with abstinence at 6 months were being male, not smoking during hospitalization, being very confident in quitting, planning to quit/stay quit, smoking fewer days in the past 30 days, fewer years of smoking, and having cerebrovascular or connective tissue rheumatic disease as primary hospital diagnosis.

CONCLUSIONS

Lack of difference between treatment arms suggests a strong effect for UC, WI was not effective, or both. Low intervention engagement may be partially responsible. Self-reported abstinence rates were relatively high in both arms, although the biochemically verified rates indicate over-reporting of abstinence. These findings suggest brief bedside counseling for all hospitalized smokers is beneficial.

TRIAL REGISTRATION

This study is registered at www.clinicaltrials.gov NCT01277250.

Young Adult Utilization of a Smoking Cessation Website: An Observational Study Comparing Young and Older Adult Patterns of Use

Background

There is little research on how young adults or young adult subgroups utilize and engage with Web-based cessation interventions when trying to quit smoking. Addressing this knowledge gap is important to identify opportunities to optimize the effectiveness of online cessation programs across diverse young adult users.

Objective

This study examines utilization of the BecomeAnEX.org smoking cessation website among young adults and young adult subgroups compared with older adults to identify patterns of use by age, gender, and race/ethnicity.

Methods

Study participants were 5983 new registered users on a free smoking cessation website who were aged 18 to 70 years. Website utilization was tracked for 6 months; metrics of use included website visits, pages per visit, length of visit, and interaction with specific website features. Differences in website use by age were examined via bivariate analyses and multivariate logistic regression adjusted for age, gender, and race/ethnicity. Interactions were examined to determine differences by gender and race/ethnicity within young (18- to 24-year-olds and 25- to 34-year-olds) and older (35 years and older) adult segments.

Results

A greater percentage of young adults aged 18 to 34 years visited the site only once compared with older adults aged 35 years and older (72.05% vs 56.59%, respectively; P<.001). Young adults also spent less time on the site and viewed fewer pages than older adults. In adjusted analyses, young adults were significantly less likely than older adults to visit the site more than once (18-24 years: adjusted odds ratio [AOR] 0.58, 95% CI 0.49-0.68, P<.001; 25-34 years: AOR 0.56, 95% CI 0.50-0.64, P<.001), spend more than 3 minutes on the site (18-24 years: AOR 0.67, 95% CI 0.57-0.79, P<.001; 25-34 years: AOR 0.56, 95% CI 0.49-0.64, P<.001), view 12 or more pages (18-24 years: AOR 0.72, 95% CI 0.61-0.83; P<.001; 25-34 years: AOR 0.67, 95% CI 0.59-0.76, P<.001), utilize the BecomeAnEX.org community (18-24 years: AOR 0.61, 95% CI 0.48-0.79, P<.001; 25-34 years: AOR 0.73, 95% CI 0.60-0.88, P<.001), or utilize Separation Exercises (18-24 years: AOR 0.68, 95% CI 0.51-0.89, P<.01; 25-34 years: AOR 0.77, 95% CI 0.63-0.94, P<.01). Gender differences in utilization were more pronounced among young adults compared with older adults, with lower levels of utilization among young men than young women. For all age groups, utilization was higher among whites and African Americans than among Hispanics and other racial minorities, with one exception—BecomeAnEX.org community utilization was significantly higher among Hispanic young adults compared with white and African American young adults.

Conclusions

Results point to important areas of inquiry for future research and development efforts. Research should focus on enhancing demand and increasing engagement among younger adults and men, examining strategies for capitalizing on young adult developmental needs, and increasing utilization of effective site features among diverse young adult users.

Engagement and attrition in Internet smoking cessation interventions: Insights from a cross-sectional survey of "one-hit-wonders"

INTRODUCTION

Internet interventions can reach large numbers of individuals. However, low levels of engagement and high rates of follow-up attrition are common, presenting major challenges to evaluation. This study investigated why registrants of an Internet smoking cessation intervention did not return after joining ("one hit wonders"), and explored the impact of graduated incentives on survey response rates and responder characteristics.

METHODS

A sample of "one hit wonders" that registered on a free smoking cessation website between 2014 and 2015 were surveyed. The initial invitation contained no incentive. Subsequent invitations were sent to random subsamples of non-responders from each previous wave offering $25 and $50 respectively. Descriptive statistics characterized respondents on demographic characteristics, reasons for not returning, and length of time since last visit. Differences were investigated with Fisher's Exact tests, Kruskal-Wallis, and logistic regression.

RESULTS

Of 8779 users who received the initial invitation, 132 completed the survey (1.5%). Among those subsequently offered a $25 incentive, 127 (3.7%) responded. Among those offered a $50 incentive, 97 responded (5.7%). The most common reasons endorsed for not returning were being unable to quit (51%), not having enough time (33%), having forgotten about the website (28%), and not being ready to quit (21%). Notably, however, 23% reported not returning because they had successfully quit smoking. Paid incentives yielded a higher proportion of individuals who were still smoking than the $0 incentive (72% vs. 61%). Among $0 and $25 responders, likelihood of survey response decreased with time since registration; the $50 incentive removed the negative effect of time-since-registration on probability of response.

CONCLUSIONS

One third of participants that had disengaged from an Internet intervention reported abstinence at follow-up, suggesting that low levels of engagement are not synonymous with treatment failure in all cases. Paid incentives above $25 may be needed to elicit survey responses, especially among those with longer intervals of disengagement from an intervention.

Systematic review and meta-analysis of Internet interventions for smoking cessation among adults

BACKGROUND

The aim of this systematic review was to determine the effectiveness of Internet interventions in promoting smoking cessation among adult tobacco users relative to other forms of intervention recommended in treatment guidelines.

METHODS

This review followed Cochrane Collaboration guidelines for systematic reviews. Combinations of "Internet," "web-based," and "smoking cessation intervention" and related keywords were used in both automated and manual searches. We included randomized trials published from January 1990 through to April 2015. A modified version of the Cochrane risk of bias assessment tool was used. We calculated risk ratios (RRs) for each study. Meta-analysis was conducted using random-effects method to pool RRs. Presentation of results follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

Forty randomized trials involving 98,530 participants were included. Most trials had a low risk of bias in most domains. Pooled results comparing Internet interventions to assessment-only/waitlist control were significant (RR 1.60, 95% confidence interval [CI] 1.15-2.21, I (2)=51.7%; four studies). Pooled results of largely static Internet interventions compared to print materials were not significant (RR 0.83, 95% CI 0.63-1.10, I (2)=0%; two studies), whereas comparisons of interactive Internet interventions to print materials were significant (RR 2.10, 95% CI 1.25-3.52, I (2)=41.6%; two studies). No significant effects were observed in pooled results of Internet interventions compared to face-to-face counseling (RR 1.35, 95% CI 0.97-1.87, I (2)=0%; four studies) or to telephone counseling (RR 0.95, 95% CI 0.79-1.13, I (2)=0%; two studies). The majority of trials compared different Internet interventions; pooled results from 15 such trials (24 comparisons) found a significant effect in favor of experimental Internet interventions (RR 1.16, 95% CI 1.03-1.31, I (2)=76.7%).

CONCLUSION

Internet interventions are superior to other broad reach cessation interventions (ie, print materials), equivalent to other currently recommended treatment modes (telephone and in-person counseling), and they have an important role to play in the arsenal of tobacco-dependence treatments.

Use and effectiveness of quitlines versus Web-based tobacco cessation interventions among 4 state tobacco control programs

BACKGROUND

Comparative effectiveness studies of state tobacco quitlines and Web-based tobacco cessation interventions are limited. In 2009, the US Centers for Disease Control and Prevention undertook a study of the comparative effectiveness of state quitlines and Web-based tobacco cessation interventions.

METHODS

Standardized questionnaires were administered to smokers who enrolled exclusively in either quitlines or Web-based tobacco cessation services in 4 states in 2011-2012. The primary outcome was the 30-day point prevalence abstinence (PPA) rate at 7 months both between and within interventions.

RESULTS

A total of 4086 participants were included in the analysis. Quitline users were significantly older, more heterogeneous in terms of race and ethnicity, less educated, less likely to be employed, and more often single than Web-based users. The 7-month 30-day PPA rate was 32% for quitline users and 27% for Web-based users. Multivariate models comparing 30-day PPA rates between interventions indicated that significantly increased odds of quitting were associated with being partnered, not living with another smoker, low baseline cigarette use, and more interactions with the intervention. After adjustments for demographic and tobacco use characteristics, quitline users had 1.26 the odds of being abstinent in comparison with Web-based users (95% confidence interval, 1.00-1.58; P = .053).

CONCLUSIONS

This is one of the largest comparative effectiveness studies of state tobacco cessation interventions to date. These findings will help public health agencies develop and tailor evidence-based tobacco cessation programs. Further research should focus on users of Web-based cessation interventions sponsored by state health departments and their cost-effectiveness.

Combined pharmacotherapy and behavioural interventions for smoking cessation

BACKGROUND

Both behavioural support (including brief advice and counselling) and pharmacotherapies (including nicotine replacement therapy (NRT), varenicline and bupropion) are effective in helping people to stop smoking. Combining both treatment approaches is recommended where possible, but the size of the treatment effect with different combinations and in different settings and populations is unclear.

OBJECTIVES

To assess the effect of combining behavioural support and medication to aid smoking cessation, compared to a minimal intervention or usual care, and to identify whether there are different effects depending on characteristics of the treatment setting, intervention, population treated, or take-up of treatment.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register in July 2015 for records with any mention of pharmacotherapy, including any type of NRT, bupropion, nortriptyline or varenicline.

SELECTION CRITERIA

Randomized or quasi-randomized controlled trials evaluating combinations of pharmacotherapy and behavioural support for smoking cessation, compared to a control receiving usual care or brief advice or less intensive behavioural support. We excluded trials recruiting only pregnant women, trials recruiting only adolescents, and trials with less than six months follow-up.

DATA COLLECTION AND ANALYSIS

Search results were prescreened by one author and inclusion or exclusion of potentially relevant trials was agreed by two authors. Data was extracted by one author and checked by another.The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically validated rates if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a Mantel-Haenszel fixed-effect model.

MAIN RESULTS

Fifty-three studies with a total of more than 25,000 participants met the inclusion criteria. A large proportion of studies recruited people in healthcare settings or with specific health needs. Most studies provided NRT. Behavioural support was typically provided by specialists in cessation counselling, who offered between four and eight contact sessions. The planned maximum duration of contact was typically more than 30 minutes but less than 300 minutes. Overall, studies were at low or unclear risk of bias, and findings were not sensitive to the exclusion of any of the six studies rated at high risk of bias in one domain. One large study (the Lung Health Study) contributed heterogeneity due to a substantially larger treatment effect than seen in other studies (RR 3.88, 95% CI 3.35 to 4.50). Since this study used a particularly intensive intervention which included extended availability of nicotine gum, multiple group sessions and long term maintenance and recycling contacts, the results may not be comparable with the interventions used in other studies, and hence it was not pooled in other analyses. Based on the remaining 52 studies (19,488 participants) there was high quality evidence (using GRADE) for a benefit of combined pharmacotherapy and behavioural treatment compared to usual care, brief advice or less intensive behavioural support (RR 1.83, 95% CI 1.68 to 1.98) with moderate statistical heterogeneity (I² = 36%).The pooled estimate for 43 trials that recruited participants in healthcare settings (RR 1.97, 95% CI 1.79 to 2.18) was higher than for eight trials with community-based recruitment (RR 1.53, 95% CI 1.33 to 1.76). Compared to the first version of the review, previous weak evidence of differences in other subgroup analyses has disappeared. We did not detect differences between subgroups defined by motivation to quit, treatment provider, number or duration of support sessions, or take-up of treatment.

AUTHORS' CONCLUSIONS

Interventions that combine pharmacotherapy and behavioural support increase smoking cessation success compared to a minimal intervention or usual care. Updating this review with an additional 12 studies (5,000 participants) did not materially change the effect estimate. Although trials differed in the details of their populations and interventions, we did not detect any factors that modified treatment effects apart from the recruitment setting. We did not find evidence from indirect comparisons that offering more intensive behavioural support was associated with larger treatment effects.

Additional behavioural support as an adjunct to pharmacotherapy for smoking cessation

BACKGROUND

Effective pharmacotherapies are available to help people who are trying to stop smoking, but quitting can still be difficult and providing higher levels of behavioural support may increase success rates further.

OBJECTIVES

To evaluate the effect of increasing the intensity of behavioural support for people using smoking cessation medications, and to assess whether there are different effects depending on the type of pharmacotherapy, or the amount of support in each condition.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register in May 2015 for records with any mention of pharmacotherapy, including any type of nicotine replacement therapy (NRT), bupropion, nortriptyline or varenicline that evaluated the addition of personal support or compared two or more intensities of behavioural support.

SELECTION CRITERIA

Randomized or quasi-randomized controlled trials in which all participants received pharmacotherapy for smoking cessation and conditions differed by the amount of behavioural support. The intervention condition had to involve person-to-person contact. The control condition could receive less intensive personal contact, or just written information. We did not include studies that used a contact-matched control to evaluate differences between types or components of support. We excluded trials recruiting only pregnant women, trials recruiting only adolescents, and trials with less than six months follow-up.

DATA COLLECTION AND ANALYSIS

One author prescreened search results and two authors agreed inclusion or exclusion of potentially relevant trials. One author extracted data and another checked them.The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates if available. We calculated the risk ratio (RR) and 95% confidence interval (CI) for each study. Where appropriate, we performed meta-analysis using a Mantel-Haenszel fixed-effect model.

MAIN RESULTS

Forty-seven studies met the inclusion criteria with over 18,000 participants in the relevant arms. There was little evidence of statistical heterogeneity (I² = 18%) so we pooled all studies in the main analysis. There was evidence of a small but statistically significant benefit from more intensive support (RR 1.17, 95% CI 1.11 to 1.24) for abstinence at longest follow-up. All but four of the included studies provided four or more sessions of support to the intervention group. Most trials used NRT. We did not detect significant effects for studies where the pharmacotherapy was nortriptyline (two trials) or varenicline (one trial), but this reflects the absence of evidence.In subgroup analyses, studies that provided at least four sessions of personal contact for the intervention and no personal contact for the control had slightly larger estimated effects (RR 1.25, 95% CI 1.08 to 1.45; 6 trials, 3762 participants), although a formal test for subgroup differences was not significant. Studies where all intervention counselling was via telephone (RR 1.28, 95% CI 1.17 to 1.41; 6 trials, 5311 participants) also had slightly larger effects, and the test for subgroup differences was significant, but this subgroup analysis was not prespecified. In this update, the benefit of providing additional behavioural support was similar for the subgroup of trials in which all participants, including controls, had at least 30 minutes of personal contact (RR 1.18, 95% CI 1.06 to 1.32; 21 trials, 5166 participants); previously the evidence of benefit in this subgroup had been weaker. This subgroup was not prespecified and a test for subgroup differences was not significant. We judged the quality of the evidence to be high, using the GRADE approach. We judged a small number of trials to be at high risk of bias on one or more domains, but findings were not sensitive to their exclusion.

AUTHORS' CONCLUSIONS

Providing behavioural support in person or via telephone for people using pharmacotherapy to stop smoking has a small but important effect. Increasing the amount of behavioural support is likely to increase the chance of success by about 10% to 25%, based on a pooled estimate from 47 trials. Subgroup analysis suggests that the incremental benefit from more support is similar over a range of levels of baseline support.

Predictors of Utilization of a Novel Smoking Cessation Smartphone App

BACKGROUND

Understanding the characteristics of high and low utilizers of smartphone applications (apps) for smoking cessation would inform development of more engaging and effective apps, yet no studies to date have addressed this critical question. Informed by prior research on predictors of cessation Web site utilization, this study examines the degree to which baseline demographic factors (gender, age, and education), smoking-related factors (smoking level and friends' smoking), and psychological factors (depression and anxiety) are predictive of utilization of a smartphone app for smoking cessation called SmartQuit.

MATERIALS AND METHODS

Data came from 98 participants randomized to SmartQuit as part of a pilot trial from March to May 2013. We used negative binomial count regressions to examine the relationship between user characteristics and utilization of the app over an 8-week treatment period.

RESULTS

Lower education (risk ratio [RR]=0.492; p=0.021), heavier smoking (RR=0.613; p=0.033), and depression (RR=0.958; p=0.017) prospectively predicted lower app utilization. Women (RR=0.320; p=0.022), those with lower education (RR=0.491; p=0.013), and heavier smokers (RR=0.418; p=0.039) had lower utilization of app features known to predict smoking cessation.

CONCLUSIONS

Many of the predictors of utilization of smoking cessation apps are the same as those of cessation Web sites. App-delivered smoking cessation treatment effectiveness could be enhanced by focusing on increasing engagement of women, those with lower education, heavy smokers, and those with current depressive symptoms.

Mechanisms of change associated with technology-based interventions for substance use

BACKGROUND

Technology-based interventions (TBIs) for substance use disorders have been increasing steadily. The mechanisms by which TBIs produce change in substance use outcomes have not been reviewed. This article is the first review of the conceptual and empirical underpinnings of the mechanisms associated with TBIs for substance use disorders.

METHODS

We review the literature on potential mechanisms associated with TBIs targeting tobacco, alcohol, and poly-substance use. We did not identify TBIs targeting other drug classes and that assessed mechanisms.

RESULTS

Research suggests that TBIs impact outcomes via similar potential mechanisms as in non-TBIs (e.g., in-person treatment), with the exception of substance use outcomes being associated with changes in the quality of coping skills. The most frequent potential mechanisms detected were self-efficacy for tobacco abstinence and perceived peer drinking for alcohol abstinence.

CONCLUSIONS

Research on mechanisms associated with TBIs is still in a nascent stage. We provide several recommendations for future work, including broadening the range of mechanisms assessed and increasing the frequency of assessment to detect temporal relations between mechanisms and outcomes. We also discuss unique challenges and opportunities afforded by technology that can advance theory, method, and clinical practice.

Telehealth interventions to reduce management complications in type 1 diabetes: A review

Type 1 diabetes is a chronic illness with a high burden of care. While effective interventions and recommendations for diabetes care exist, the intensive nature of diabetes management makes compliance difficult. This is especially true in children and adolescents as they have unique psychosocial and diabetes needs. Despite the development of effective in-person interventions targeting improving self-management and ameliorating psychosocial difficulties there are still a number of barriers to implementing these interventions, namely time, cost, and access. Telehealth interventions allow for the dissemination of these interventions to a broader audience. Self-management and psychosocial telehealth interventions are reviewed with a special emphasis on mobile phone and internet based technology use. While efficacy has been demonstrated in a number of telehealth interventions with improved cost effectiveness over in-person interventions, many challenges remain including high participant attrition and difficulties with receiving reimbursement for services rendered. These and other challenges are discussed with recommendations for researchers and telehealth providers provided.

The Missing=Smoking Assumption: A Fallacy in Internet-Based Smoking Cessation Trials?

INTRODUCTION

In this study, penalized imputation (PI), a common approach to handle missing smoking status data and sometimes referred to as "missing=smoking," is compared with other missing data approaches using data from internet-based smoking cessation trials. Two hypotheses were tested: (1) PI leads to more conservative effect estimates than complete observations analysis; and (2) PI and multiple imputation (MI) lead to similar effect estimates under balanced (equal missingness proportions among the trial arms) and unbalanced missingness.

METHODS

First, the outcomes of 22 trials included in a recent Cochrane review on internet-based smoking cessation interventions were reanalyzed using only the complete observations, and after applying PI. Second, in a simulation study outcomes under PI, complete observations analysis, and two types of MI were compared. For this purpose, individual patient data from one of the Cochrane review trials were used. Results of the missing data approaches were compared with reference data without missing observations, upon which balanced and unbalanced missingness scenarios were imposed.

RESULTS

In the reanalysis of 22 trials, relative risks (RR = 1.15 [1.00; 1.33]) after PI were nearly identical to those under complete observations analysis (RR = 1.14 [0.98; 1.32]). In the simulation study, PI was the only approach that led to deviations from the reference data beyond its 95% confidence interval.

CONCLUSIONS

Analyses after PI led to pooled results equivalent to complete observations analyses. PI also led to significant deviations from the reference in the simulation studies. PI biases the reported effects of interventions, favoring the condition with the lowest proportion of missingness. Therefore, more sophisticated missing data approaches than PI should be applied.

Effects of a guided web-based smoking cessation program with telephone counseling: a cluster randomized controlled trial

Background

Preliminary findings suggest that Web-based interventions may be effective in achieving significant smoking cessation. To date, very few findings are available for primary care patients, and especially for the involvement of general practitioners.

Objective

Our goal was to examine the short-term effectiveness of a fully automated Web-based coaching program in combination with accompanied telephone counseling in smoking cessation in a primary care setting.

Methods

The study was an unblinded cluster-randomized trial with an observation period of 12 weeks. Individuals recruited by general practitioners randomized to the intervention group participated in a Web-based coaching program based on education, motivation, exercise guidance, daily short message service (SMS) reminding, weekly feedback through Internet, and active monitoring by general practitioners. All components of the program are fully automated. Participants in the control group received usual care and advice from their practitioner without the Web-based coaching program. The main outcome was the biochemically confirmed smoking status after 12 weeks.

Results

We recruited 168 participants (86 intervention group, 82 control group) into the study. For 51 participants from the intervention group and 70 participants from the control group, follow-up data were available both at baseline and 12 weeks. Very few patients (9.8%, 5/51) from the intervention group and from the control group (8.6%, 6/70) successfully managed smoking cessation (OR 0.86, 95% CI 0.25-3.0; P=.816). Similar results were found within the intent-to-treat analysis: 5.8% (5/86) of the intervention group and 7.3% (6/82) of the control group (OR 1.28, 95% CI 0.38-4.36; P=.694). The number of smoked cigarettes per day decreased on average by 9.3 in the intervention group and by 6.6 in the control group (2.7 mean difference; 95% CI -5.33 to -0.58; P=.045). After adjustment for the baseline value, age, gender, and height, this significance decreases (mean difference 2.2; 95% CI -4.7 to 0.3; P=.080).

Conclusions

This trial did not show that the tested Web-based intervention was effective for achieving smoking cessation compared to usual care. The limited statistical power and the high drop-out rate may have reduced the study’s ability to detect significant differences between the groups. Further randomized controlled trials are needed in larger populations and to investigate the long-term outcome.

Trial Registration

German Register for Clinical Trials, registration number DRKS00003067; http://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ ID=DRKS00003067 (Archived by WebCite at http://www.webcitation.org/6Sff1YZpx).

Outcome predictors of Internet-based brief sex therapy for sexual dysfunctions in heterosexual men

The authors investigated whether baseline and therapy process characteristics of 82 heterosexual men participating in an Internet-based sex therapy study predict posttreatment sexual functioning. Problem severity, baseline sexual desire and baseline sexual satisfaction, but also partner problems and quality of the therapeutic relationship are predictive for sexual functioning and sexual satisfaction after finishing Internet-based sex therapy. The obtained outcome predictors could benefit men with sexual dysfunctions by tailoring online therapy programs to their individual characteristics. In addition, therapists should realize that clients suffering from erectile dysfunction or premature ejaculation in online sex therapy attach great importance to the therapeutic relationship.

A review of web based interventions for managing tobacco use

Web based interventions (WBIs) have been developed for various health conditions. These include interventions for various psychoactive substance use disorders including tobacco and alcohol. Tobacco use has remained the single largest preventable cause of global mortality and morbidity for many years. It is responsible for around 6 million deaths annually world-wide. Ironically, most of the tobacco users reside in resource poor low and middle-income countries. The article reviews the existing literature on WBIs for management of tobacco use. The literature search was performed using MedLine, PubMed, PsycINFO, Embase and Cochrane Review for relevant English language articles published from 1998 up to 2013. There is limited support for effectiveness of WBIs for managing tobacco use among adolescents. Although most of the trials among adults found WBIs to be more effective at short term follow-up (a few days to weeks), the benefits failed to extend beyond 3 months in most of the studies. All but one interventions studied in a randomized controlled trial is for smoking forms.

Choosing your network: social preferences in an online health community

A growing number of online health communities offer individuals the opportunity to receive information, advice, and support from peers. Recent studies have demonstrated that these new online contacts can be important informational resources, and can even exert significant influence on individuals' behavior in various contexts. However little is known about how people select their health contacts in these virtual domains. This is because selection preferences in peer networks are notoriously difficult to detect. In existing networks, unobserved pressures on tie formation--such as common organizational memberships, introductions to friends of friends, or limitations on accessibility--may mistakenly be interpreted as individual preferences for interacting/not interacting with others. We address these issues by adopting a social media approach to studying network formation. We study social selection using an in vivo study within an online exercise program, in which anonymous participants have equal opportunities for initiating relationships with other program members. This design allows us to identify individuals' preferences for health contacts, and to evaluate what these preferences imply for members' access to new kinds of health information, and for the kinds of social influences to which they are exposed. The study was conducted within a goal-oriented fitness competition, in which participation was greatest among a small core of active individuals. Our results show that the active participants displayed indifference to the fitness and exercise profiles of others, disregarding information about others' fitness levels, exercise preferences, and workout experiences, instead selecting partners almost entirely on the basis of similarities on gender, age, and BMI. Interestingly, the findings suggest that rather than expanding and diversifying their sources of health information, participants' choices limited the value of their online resources by selecting contacts based on characteristics that are common sources of homophily in offline relationships. In light of our findings, we discuss design principles that may be useful for organizations and policy makers trying to improve the value of participants' social capital within online health programs.

Usage and effectiveness of a fully automated, open-access, Spanish Web-based smoking cessation program: randomized controlled trial

BACKGROUND

The Internet is an optimal setting to provide massive access to tobacco treatments. To evaluate open-access Web-based smoking cessation programs in a real-world setting, adherence and retention data should be taken into account as much as abstinence rate.

OBJECTIVE

The objective was to analyze the usage and effectiveness of a fully automated, open-access, Web-based smoking cessation program by comparing interactive versus noninteractive versions.

METHODS

Participants were randomly assigned either to the interactive or noninteractive version of the program, both with identical content divided into 4 interdependent modules. At baseline, we collected demographic, psychological, and smoking characteristics of the smokers self-enrolled in the Web-based program of Universidad Nacional de Educación a Distancia (National Distance Education University; UNED) in Madrid, Spain. The following questionnaires were administered: the anxiety and depression subscales from the Symptom Checklist-90-Revised, the 4-item Perceived Stress Scale, and the Heaviness of Smoking Index. At 3 months, we analyzed dropout rates, module completion, user satisfaction, follow-up response rate, and self-assessed smoking abstinence.

RESULTS

A total of 23,213 smokers were registered, 50.06% (11,620/23,213) women and 49.94% (11,593/23,213) men, with a mean age of 39.5 years (SD 10.3). Of these, 46.10% (10,701/23,213) were married and 34.43% (7992/23,213) were single, 46.03% (10,686/23,213) had university education, and 78.73% (18,275/23,213) were employed. Participants smoked an average of 19.4 cigarettes per day (SD 10.3). Of the 11,861 smokers randomly assigned to the interactive version, 2720 (22.93%) completed the first module, 1052 (8.87%) the second, 624 (5.26%) the third, and 355 (2.99%) the fourth. Completion data was not available for the noninteractive version (no way to record it automatically). The 3-month follow-up questionnaire was completed by 1085 of 23,213 enrolled smokers (4.67%). Among them, 406 (37.42%) self-reported not smoking. No difference between groups was found. Assuming missing respondents continued to smoke, the abstinence rate was 1.74% (406/23,213), in which 22,678 were missing respondents. Among follow-up respondents, completing the 4 modules of the intervention increased the chances of smoking cessation (OR 1.95, 95% CI 1.27-2.97, P<.001), as did smoking 30 minutes (OR 1.58, 95% CI 1.04-2.39, P=.003) or 1 hour after waking (OR 1.93, 95% CI 1.27-2.93, P<.001) compared to smoking within the first 5 minutes after waking.

CONCLUSIONS

The findings suggest that the UNED Web-based smoking cessation program was very accessible, but a high level of attrition was confirmed. This could be related to the ease of enrollment, its free character, and the absence of direct contact with professionals. It is concluded that, in practice, the greater the accessibility to the program, the lower the adherence and retention. Professional support from health services and the payment of a reimbursable fee could prevent high rates of attrition.

Exploring the "active ingredients" of an online smoking intervention: a randomized factorial trial

INTRODUCTION

Research needs to systematically identify which components increase online intervention effectiveness (i.e., active ingredients). This study explores the effects of 4 potentially important design features in an Internet-based, population-level smoking intervention.

METHODS

Smokers (n = 1,865) were recruited from a large health care organization, regardless of readiness to quit. Using a full factorial design, participants were randomized to 1 of the 2 levels of each experimental factor (message tone [prescriptive vs. motivational], navigation autonomy [dictated vs. not], e-mail reminders [yes vs. no], and receipt of personally tailored testimonials [yes vs. no]) and provided access to the online intervention. Primary outcomes were self-reported 7-day point-prevalent smoking abstinence and confirmed utilization of adjunct treatment (pharmacotherapy or phone counseling) available through the health plan at 1 year. Outcomes were also assessed at 2 and 6 months and were examined among all enrolled participants (intent-to-treat [ITT]) and all who viewed the intervention (modified ITT).

RESULTS

At 1 year, 13.7% were abstinent and 26.0% utilized adjunct treatment. None of the contrasting factor levels differentially influenced abstinence or treatment utilization at 12 months. In the modified ITT sample, smokers receiving testimonials were less likely to use adjunct treatment at 6 months (odds ratio = 0.54, 95% confidence interval = 0.30-0.98, p = .04).

CONCLUSIONS

None of the design features enhanced treatment outcome. The negative effect observed for testimonials is provocative, but it should be viewed with caution. This study offers a model for future research testing the "active ingredients" of online interventions.

Do email and mobile phone prompts stimulate primary school children to reuse an Internet-delivered smoking prevention intervention?

BACKGROUND

Improving the use (eg, initial visit and revisits) of Internet-delivered interventions to promote healthy lifestyles such as non-smoking is one of the largest challenges in the field of eHealth. Prompts have shown to be effective in stimulating reuse of Internet-delivered interventions among adults and adolescents. However, evidence concerning effectiveness of prompts to promote reuse of a website among children is still scarce.

OBJECTIVE

The aim of this study is to investigate (1) whether prompts are effective in promoting reuse of an intervention website containing information on smoking prevention for children, (2) whether the content of the prompt is associated with its effect in terms of reuse, and (3) whether there are differences between children who do or do not respond to prompts.

METHODS

The sample of this cluster-randomized study consisted of 1124 children (aged 10-11 years) from 108 Dutch primary schools, who were assigned to the experimental group of an Internet-delivered smoking prevention intervention study. All participants completed a Web-based questionnaire on factors related to (non-)smoking. Schools were randomized to a no-prompt group (n=50) or a prompt group (n=58). All children could revisit the intervention website, but only the children in the prompt group received email and SMS prompts to revisit the website. Those prompt messages functioned as a teaser to stimulate reuse of the intervention website. Reuse of the website was objectively tracked by means of a server registration system. Repeated measures analysis of variance and linear regression analysis were performed to assess the effects of prompts on website reuse and to identify individual characteristics of participants who reuse the intervention website.

RESULTS

Children in the prompt group reused the intervention website significantly more often compared to children in the no-prompt group (B=1.56, P<.001). Prompts announcing new animated videos (F1,1122=9.33, P=.002) and games about (non-)smoking on the website (F1,1122=8.28, P=.004) resulted in most reuse of the website. Within the prompt group, children with a low socioeconomic status (SES) reused the intervention website more often (B=2.19, P<.001) than children of high SES (B=0.93, P=.005).

CONCLUSIONS

Prompts can stimulate children to reuse an intervention website aimed at smoking prevention. Prompts showed, furthermore, to stimulate children of a low SES slightly more to reuse an intervention website, which is often a difficult target group in terms of stimulating participation. However, the number of revisits was quite low, which requires further study into how prompts can be optimized in terms of content and frequency to improve the number of revisits.

TRIAL REGISTRATION

Netherlands Trial Register Number: NTR3116; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=3116 (Archived by WebCite at http://www.webcitation.org/6O0wQYuPI).

Systematic literature review of Internet interventions across health behaviors

Purpose: This review examines Internet interventions aiming to change health behaviors in the general population. Methods: Internet health interventions in the USA published between January 2005 and December 2013 were identified through Medline and CINAHL. Keywords used were (Internet or e-health or social media or web) paired with (intervention or program*). A total of 38 articles met all criteria and were reviewed. Results: Studies were analyzed by targeted health behavior interventions: tobacco (5), alcohol (4), weight loss (7), physical activity (PA) (7), nutrition (2), PA and nutrition combined (5), HIV or sexual health (4), and chronic diseases (4). Interventions ranged from one session to 24  weeks (average 6-12 weeks). Common strategies used, including web-based information, tailored feedback, weekly e-mails, goal setting, and self-assessment. Social cognitive theory and the transtheoretical models were the most commonly used frameworks. Recruitment strategies were typically media based varied by settings and populations. Except for the tobacco interventions, the majority studies yielded significant outcomes. Conclusion: This review provides updates and synthesized knowledge on the design and consistent effectiveness of Internet interventions across health behaviors. Results have implications for public health and healthcare professionals, as they play a key role in developing and delivering health promotion interventions as well as in assisting the communities and clients serviced obtaining evidence-based health information.

An innovative team-based stop smoking competition among Māori and Pacific Island smokers: rationale and method for the study and its evaluation

BACKGROUND

Māori and Pacific Island people have significantly higher smoking rates compared to the rest of the New Zealand population. The main aim of this paper is to describe how knowledge of Indigenous people's practices and principles can be combined with proven effective smoking cessation support into a cessation intervention appropriate for Indigenous people.

METHODS/DESIGN

A literature review was conducted to identify what cultural principles and practices could be used to increase salience, and what competition elements could have an impact on efficacy of smoking cessation. The identified elements were incorporated into the design of a cessation intervention.

DISCUSSION

Cultural practices incorporated into the intervention include having a holistic family or group-centred focus, inter-group competitiveness, fundraising and ritual pledging. Competition elements included are social support, pharmacotherapy use, cash prize incentives and the use of a dedicated website and iPad application. A pre-test post-test will be combined with process evaluation to evaluate if the competition results in triggering mass-quitting, utilisation of pharmacotherapy and in increasing sustained smoking cessation and to get a comprehensive understanding of the way in which they contribute to the effect. The present study is the first to describe how knowledge about cultural practices and principles can be combined with proven cessation support into a smoking cessation contest. The findings from this study are promising and further more rigorous testing is warranted.

Initial impact of tailored web-based messages about cigarette smoke and breast cancer risk on boys' and girls' risk perceptions and information seeking: randomized controlled trial

Background

Recent evidence indicates a causal link between both active smoking and secondhand smoke (SHS) exposure and breast cancer (BC).

Objective

The objective of the present study was to evaluate the initial reactions of girls and boys to tailored Web-based messages that describe the relationship between SHS and BC, using a parallel, single-blinded cluster randomized controlled trial.

Methods

This trial was nested within a cycle of an ongoing longitudinal study of 1498 students from 74 secondary schools. Self-reported assessments were used to evaluate the impact of study messages on participants’ risk perception and interest in obtaining additional information after participants were randomized by schools to control or intervention groups. The intervention group received a tailored visual message (based on gender and Aboriginal status) about BC and tobacco smoke. The control group received a standard visual message about smoking and cancer.

Results

SHS exposure was identified as a BC risk factor by 380/1488 (25.54%) participants, during the preintervention analysis. Compared to the female participants in the control group (491/839, 58.5%), girls who received the intervention (339/649, 52.2%) were 14% more likely to agree that exposure to SHS increased their BC risk (relative risk [RR] 1.14, 95% CI 1.07-1.21). Nonsmoking girls who received the intervention were 14% more likely to agree that starting smoking would increase their BC risk (RR 1.14, 95% CI 1.07-1.21). Compared to the male participants in control group (348/839, 41.5%), boys who received the intervention (310/649, 47.8%) were 10% more likely to agree that girls’ exposure to SHS increased their BC risk (RR 1.10, 95% CI 1.02-1.18). Compared to controls, girls who received the intervention were 52% more likely to request additional information about SHS and BC (RR 1.52, 95% CI 1.12-2.06).

Conclusions

Brief gender-sensitive messages delivered via the Internet have the potential to increase awareness and to stimulate information seeking about the risk for BC associated with SHS.