Randomized controlled trial of an interactive internet smoking cessation program with long-term follow-up

A meta-analysis of the effect of substance use interventions on emotion outcomes

OBJECTIVE

Emotional distress has been posited as a key underlying mechanism in the development and maintenance of substance use disorder (SUD), and patients seeking SUD treatment are often experiencing high levels of negative emotion and/or low levels of positive emotion. But the extent to which SUD interventions impact emotional outcomes among general SUD populations is yet unquantified. The current meta-analysis aims to fill this gap.

METHOD

A total of 11,754 records were screened for randomized, controlled trials examining the effect of behavioral SUD interventions on emotion outcomes. Our search yielded a total of 138 effect sizes calculated based on data from 5,146 individuals enrolled in 30 independent clinical trials. Random-effects meta-analysis was used to calculate pooled effect sizes, and metaregression analyses examined study-level moderators (e.g., intervention type).

RESULTS

Findings indicated a small but significant effect of SUD interventions on emotion outcomes, d = 0.157, 95% CI [0.052, 0.262] (k = 30). The effect size for negative emotion was nominally bigger, d = 0.162, 95% CI [0.056, 0.269] (k = 30), whereas the effect for positive emotion did not reach statistical significance, d = 0.062, 95% CI [-0.089, 0.213] (k = 7). Studies featuring SUD interventions designed to specifically target emotions (i.e., affect-regulation, mindfulness-based treatments) produced larger reductions in negative emotion compared with studies featuring interventions that did not contain specific emotion modules (e.g., contingency management).

CONCLUSIONS

Findings suggest that SUD interventions-especially mindfulness-based and affect-regulation treatments-indeed significantly reduce negative emotion, although relatively small effect sizes indicate potential room for improvement. Conclusions regarding positive emotion should be considered preliminary because of the limited numbers of samples assessing these outcomes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Comparing Treatment Acceptability and 12-Month Cessation Rates in Response to Web-Based Smoking Interventions Among Smokers Who Do and Do Not Screen Positive for Affective Disorders: Secondary Analysis

BACKGROUND

Web-based cessation programs are now common for intervening with smokers. However, it remains unclear how acceptable or effective these interventions are among people with affective disorders and symptoms (ADS; eg, depression and anxiety). Research examining this is extremely limited, with mixed results on cessation rates. Additional large studies are needed to more fully understand whether Web-based interventions are similarly used and equally effective among people with and without affective disorder symptomology. If not, more targeted Web-based interventions may be required.

OBJECTIVE

The goal of the research was to compare Web-based treatment acceptability (defined by satisfaction and use) and 12-month cessation outcomes between smokers with and without ADS.

METHODS

Participants (N=2512) were adult smokers enrolled in a randomized, comparative effectiveness trial of two Web-based smoking interventions designed for the general population of smokers. At baseline, participants reported demographic and smoking characteristics and completed measures assessing ADS. Participants were then classified into subgroups based on their self-reported ADS-either into a no ADS group or into six nonmutually exclusive subgroups: depression, posttraumatic stress disorder (PTSD), panic disorder (PD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), and more than one ADS. Surveys at 12 months postrandomization included subjective ratings of treatment acceptability and self-reported smoking cessation. Treatment use (ie, number of log-ins and total duration of exposure) was assessed via automated records.

RESULTS

Relative to the no ADS group, all six ADS subgroups reported significantly greater satisfaction with their assigned Web treatment program, but they spent less time logged in than those with no ADS. For number of log-ins, a treatment arm by ADS group interaction was observed across all ADS subgroups except GAD, suggesting that relative to the no ADS group, they logged in less to one website but not the other. At the 12-month follow-up, abstinence rates in the no ADS group (153/520, 29.42%) were significantly higher than for participants who screened positive for depression (306/1267, 24.15%; P=.03), PTSD (294/1215, 24.19%; P=.03), PD (229/1003, 23.83%; P=.009), and two or more ADS (323/1332, 24.25%; P=.03). Post hoc analyses suggest the lower quit rates may be associated with differences in baseline nicotine dependence and levels of commitment to resist smoking in difficult situations. Website use did not explain the differential abstinence rates.

CONCLUSIONS

Despite reporting higher levels of treatment satisfaction, most smokers with ADS used their assigned intervention less often and had lower quit rates than smokers with no ADS at treatment onset. The results support the need for developing more targeted interventions for smokers with ADS.

TRIAL REGISTRATION

Clinical Trials.gov NCT01812278; https://clinicaltrials.gov/ct2/show/NCT01812278 (Archived by WebCite at http://www.webcitation.org/78L9cNdG4).

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.

Good intentions are not enough: how informatics interventions can worsen inequality

Health informatics interventions are designed to help people avoid, recover from, or cope with disease and disability, or to improve the quality and safety of healthcare. Unfortunately, they pose a risk of producing intervention-generated inequalities (IGI) by disproportionately benefiting more advantaged people. In this perspective paper, we discuss characteristics of health-related interventions known to produce IGI, explain why health informatics interventions are particularly vulnerable to this phenomenon, and describe safeguards that can be implemented to improve health equity. We provide examples in which health informatics interventions produced inequality because they were more accessible to, heavily used by, adhered to, or effective for those from socioeconomically advantaged groups. We provide a brief outline of precautions that intervention developers and implementers can take to guard against creating or worsening inequality through health informatics. We conclude by discussing evaluation approaches that will ensure that IGIs are recognized and studied.

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.

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.

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.

Technology-based support via telephone or web: a systematic review of the effects on smoking, alcohol use and gambling

A systematic review of the literature on telephone or internet-based support for smoking, alcohol use or gambling was performed. Studies were included if they met the following criteria: The design being a randomized control trail (RCT), focused on effects of telephone or web based interventions, focused on pure telephone or internet-based self-help, provided information on alcohol or tobacco consumption, or gambling behavior, as an outcome, had a follow-up period of at least 3months, and included adults. Seventy-four relevant studies were found; 36 addressed the effect of internet interventions on alcohol consumption, 21 on smoking and 1 on gambling, 12 the effect of helplines on smoking, 2 on alcohol consumption, and 2 on gambling. Telephone helplines can have an effect on tobacco smoking, but there is no evidence of the effects for alcohol use or gambling. There are some positive findings regarding internet-based support for heavy alcohol use among U.S. college students. However, evidence on the effects of internet-based support for smoking, alcohol use or gambling are to a large extent inconsistent.

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.

Internet-based contingency management to promote smoking cessation: a randomized controlled study

We evaluated an Internet-based contingency management intervention to promote smoking cessation. Participants in the contingent group (n = 39) earned vouchers contingent on video confirmation of breath carbon monoxide (CO) ≤ 4 parts per million (ppm). Earnings for participants in the noncontingent group (n = 38) were independent of CO levels. Goals and feedback about smoking status were provided on participants' homepages. The median percentages of negative samples during the intervention in the noncontingent and contingent groups were 25% and 66.7%, respectively. There were no significant differences in absolute CO levels or abstinence at 3- and 6-month follow-ups. Compared to baseline, however, participants in both groups reduced CO by an estimated 15.6 ppm during the intervention phases. The results suggest that the contingency for negative COs promoted higher rates of abstinence during treatment, and that other elements of the system, such as feedback, frequent monitoring, and goals, reduced smoking.

Smoking cessation interventions for smokers with current or past depression

BACKGROUND

Individuals with current or past depression are often smokers who are more nicotine dependent, more likely to suffer from negative mood changes after nicotine withdrawal, and more likely to relapse to smoking after quitting than the general population, which contributes to their higher morbidity and mortality from smoking-related illnesses. It remains unclear what interventions can help them to quit smoking.

OBJECTIVES

To evaluate the effectiveness of smoking cessation interventions, with and without specific mood management components, in smokers with current or past depression.

SEARCH METHODS

In April 2013, we searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, PsycINFO, other reviews, and asked experts for information on trials.

SELECTION CRITERIA

Criteria for including studies in this review were that they had to be randomised controlled trials (RCTs) comparing smoking cessation interventions in adult smokers with current or past depression. Depression was defined as major depression or depressive symptoms. We included studies where subgroups of participants with depression were identified, either pre-stated or post hoc. The outcome was abstinence from smoking after six months or longer follow-up. We preferred prolonged or continuous abstinence and biochemically validated abstinence where available.

DATA COLLECTION AND ANALYSIS

When possible, we estimated pooled risk ratios (RRs) with the Mantel-Haenszel method (fixed-effect model). We also performed subgroup analyses, by length of follow-up, depression measurement, depression group in study, antidepressant use, published or unpublished data, format of intervention, level of behavioural support, additional pharmacotherapy, type of antidepressant medication, and additional nicotine replacement therapy (NRT).

MAIN RESULTS

Forty-nine RCTs were included of which 33 trials investigated smoking cessation interventions with specific mood management components for depression. In smokers with current depression, meta-analysis showed a significant positive effect for adding psychosocial mood management to a standard smoking cessation intervention when compared with standard smoking cessation intervention alone (11 trials, N = 1844, RR 1.47, 95% CI 1.13 to 1.92). In smokers with past depression we found a similar effect (13 trials, N = 1496, RR 1.41, 95% CI 1.13 to 1.77). Meta-analysis resulted in a positive effect, although not significant, for adding bupropion compared with placebo in smokers with current depression (5 trials, N = 410, RR 1.37, 95% CI 0.83 to 2.27). There were not enough trial data to evaluate the effectiveness of fluoxetine and paroxetine for smokers with current depression. Bupropion (4 trials, N = 404, RR 2.04, 95% CI 1.31 to 3.18) might significantly increase long-term cessation among smokers with past depression when compared with placebo, but the evidence for bupropion is relatively weak due to the small number of studies and the post hoc subgroups for all the studies. There were not enough trial data to evaluate the effectiveness of fluoxetine, nortriptyline, paroxetine, selegiline, and sertraline in smokers with past depression.Twenty-three of the 49 trials investigated smoking cessation interventions without specific components for depression. There was heterogeneity between the trials which compared psychosocial interventions with standard smoking cessation counselling for both smokers with current and past depression. Therefore, we did not estimate a pooled effect. One trial compared nicotine replacement therapy (NRT) versus placebo in smokers with current depression and found a positive, although not significant, effect (N = 196, RR 2.64, 95% CI 0.93 to 7.45). Meta-analysis also found a positive, although not significant, effect for NRT versus placebo in smokers with past depression (3 trials, N = 432, RR 1.17, 95% CI 0.85 to 1.60). Three trials compared other pharmacotherapy versus placebo and six trials compared other interventions in smokers with current or past depression. Due to heterogeneity between the interventions of the included trials we did not estimate pooled effects.

AUTHORS' CONCLUSIONS

Evidence suggests that adding a psychosocial mood management component to a standard smoking cessation intervention increases long-term cessation rates in smokers with both current and past depression when compared with the standard intervention alone. Pooled results from four trials suggest that use of bupropion may increase long-term cessation in smokers with past depression. There was no evidence found for the use of bupropion in smokers with current depression. There was not enough evidence to evaluate the effectiveness of the other antidepressants in smokers with current or past depression. There was also not enough evidence to evaluate the group of trials that investigated interventions without specific mood management components for depression, including NRT and psychosocial interventions.

Internet-based interventions for smoking cessation

BACKGROUND

The Internet is now an indispensable part of daily life for the majority of people in many parts of the world. It offers an additional means of effecting changes to behaviour such as smoking.

OBJECTIVES

To determine the effectiveness of Internet-based interventions for smoking cessation.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialized Register. There were no restrictions placed on language of publication or publication date. The most recent search was conducted in April 2013.

SELECTION CRITERIA

We included randomized and quasi-randomized trials. 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.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed and extracted data. Methodological and study quality details were extracted using a standardized form. We extracted smoking cessation outcomes of six months follow-up or more, reporting short-term outcomes where longer-term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI). Clinical and statistical heterogeneity limited our ability to pool studies.

MAIN RESULTS

This updated review includes a total of 28 studies with over 45,000 participants. Some Internet programmes were intensive and included multiple outreach contacts with participants, whilst others relied on participants to initiate and maintain use.Fifteen trials compared an Internet intervention to a non-Internet-based smoking cessation intervention or to a no-intervention control. Ten of these recruited adults, one recruited young adult university students and two recruited adolescents. Seven of the trials in adults had follow-up at six months or longer and compared an Internet intervention to usual care or printed self help. In a post hoc subgroup analysis, pooled results from three trials that compared interactive and individually tailored interventions to usual care or written self help detected a statistically significant effect in favour of the intervention (RR 1.48, 95% CI 1.11 to 2.78). However all three trials were judged to be at high risk of bias in one domain and high statistical heterogeneity was detected (I² = 53%), with no obvious clinical explanation. Pooled results from two studies of an interactive, tailored intervention involving the Internet and automated phone contacts also detected a significant effect (RR 2.05, 95% CI 1.42 to 2.97, I² = 42%). Results from a sixth study comparing an interactive but non-tailored intervention to control did not detect a significant effect, nor did the seventh study, which compared a non-interactive, non-tailored intervention to control. Three trials comparing Internet interventions to face-to-face or phone counselling also did not detect evidence of an effect, nor did two trials evaluating Internet interventions as adjuncts to other behavioural interventions. A trial in college students increased point prevalence abstinence after 30 weeks but had no effect on sustained abstinence. Two small trials in adolescents did not detect an effect on cessation compared to control.Fourteen trials, all in adult populations, compared different Internet sites or programmes. Pooled estimates from three trials that compared tailored and/or interactive Internet programmes with non-tailored, non-interactive Internet programmes did not detect evidence of an effect (RR 1.12, 95% CI 0.95 to 1.32, I² = 0%). One trial detected evidence of a benefit from a tailored email compared to a non-tailored one, whereas a second trial comparing tailored messages to a non-tailored message did not detect evidence of an effect. Trials failed to detect a benefit of including a mood management component (three trials), or an asynchronous bulletin board.

AUTHORS' CONCLUSIONS

Results suggest that some Internet-based interventions can assist smoking cessation at six months or longer, particularly those which are interactive and tailored to individuals. However, the trials that compared Internet interventions with usual care or self help did not show consistent effects and were at risk of bias. Further research is needed despite 28 studies on the subject. Future studies should carefully consider optimising the interventions which promise most effect such as tailoring and interactivity.

Two decades of smoking cessation treatment research on smokers with depression: 1990-2010

INTRODUCTION

Adults with depression smoke at higher rates than other adults leaving a large segment of this population, who already incur increased health-related risks, vulnerable to the enormous harmful consequences of smoking. Yet, the impact that depression has on smoking cessation is not clear due to the mixed results of past research. The primary aims of this review were to synthesize the research examining the relationship of depression to smoking cessation outcomes over a 20-year period, to examine the gender and racial composition of these studies, and to identify directions for future research.

METHODS

Potential articles published between January 1, 1990 and December 31, 2010 were identified through a MEDLINE search of the terms "clinical trial," "depression," and "smoking cessation." 68 studies used all three terms and met the inclusion criteria.

RESULTS

The majority of studies examined either a past diagnosis of major depression or current depression symptoms. Within the few studies that examined the interaction of gender and depression on smoking cessation, depression had a greater impact on treatment outcomes for women than men. No study reported examining the interactive impact of race and depression on treatment outcomes.

CONCLUSIONS

Although attention to the relationship of depression and smoking cessation outcomes has increased over the past 20 years, little information exists to inform a treatment approach for smokers with Current Major Depressive Disorder, Dysthymia, and Minor Depression and few studies report gender and racial differences in the relationship of depression and smoking cessation outcomes, thus suggesting major areas for targeted research.

Engagement promotes abstinence in a web-based cessation intervention: cohort study

Background

Web-based smoking cessation interventions can have a public health impact because they are both effective in promoting cessation and can reach large numbers of smokers in a cost-efficient manner. Their potential impact, however, has not been realized. It is still unclear how such interventions promote cessation, who benefits most, and how to improve their population impact.

Objective

To examine the effectiveness of a highly promoted Web-based smoking cessation intervention to promote quit behavior over time, identify the most effective features, and understand who is most likely to use those features by using unweighted and weighted analyses to estimate the impact in the broader pool of registered site users.

Methods

A sample of 1033 new adult registrants was recruited from a Web-based smoking cessation intervention by using an automated study management system. Abstinence was assessed by self-report through a mixed-mode follow-up (online survey with telephone follow-up for nonrespondents) at 1, 3, and 6 months. Software tracked respondents’ online activity. Generalized estimating equations (GEE) were used to examine predictors of website utilization and how utilization promoted abstinence using unweighted and weighted data.

Results

The 7-day point prevalence abstinence rates at 6 months ranged from 20.68% to 11.13% in the responder and intent-to-treat samples, respectively. Predictors of abstinence in unweighted analyses included number of visits to the website as well as accessing specific interactive or engaging features. In weighted analyses, only number of visits was predictive of abstinence. Motivation to quit was a key predictor of website utilization, whereas negative partner support decreased the likelihood of increasing visits or accessing engaging features.

Conclusions

Engagement is critical to promoting smoking cessation. The next generation of Web-based smoking cessation interventions needs to maximize the initial engagement of all new visitors and work to retain those smokers who proceed to register on the site.

Demand for and availability of online support to stop smoking

OBJECTIVES: Estimate the frequency of online searches on the topic of smoking and analyze the quality of online resources available to smokers interested in giving up smoking. METHODS: Search engines were used to revise searches and online resources related to stopping smoking in Brazil in 2010. The number of searches was determined using analytical tools available on Google Ads; the number and type of sites were determined by replicating the search patterns of internet users. The sites were classified according to content (advertising, library of articles and other). The quality of the sites was analyzed using the Smoking Treatment Scale- Content (STS-C) and the Smoking Treatment Scale - Rating (STS-R). RESULTS: A total of 642,446 searches was carried out. Around a third of the 113 sites encountered were of the 'library' type, i.e. they only contained articles, followed by sites containing clinical advertising (18.6) and professional education (10.6). Thirteen of the sites offered advice on quitting directed at smokers. The majority of the sites did not contain evidence-based information, were not interactive and did not have the possibility of communicating with users after the first contact. Other limitations we came across were a lack of financial disclosure as well as no guarantee of privacy concerning information obtained and no distinction made between editorial content and advertisements. CONCLUSIONS: There is a disparity between the high demand for online support in giving up smoking and the scarcity of quality online resources for smokers. It is necessary to develop interactive, customized online resources based on evidence and random clinical testing in order to improve the support available to Brazilian smokers.

Protocol of a randomized controlled trial of the Tobacco Tactics website for operating engineers

BACKGROUND

Recent research indicates that 35 percent of blue-collar workers in the US currently smoke while only 20 percent of white-collar workers smoke. Over the last year, we have been working with heavy equipment operators, specifically the Local 324 Training Center of the International Union of Operating Engineers, to study the epidemiology of smoking, which is 29% compared to 21% among the general population. For the current study funded by the National Cancer Institute (1R21CA152247-01A1), we have developed the Tobacco Tactics website which will be compared to the state supported 1-800-QUIT-NOW telephone line. Outcome evaluation will compare those randomized to the Tobacco Tactics web-based intervention to those randomized to the 1-800-QUIT-NOW control condition on: a) 30-day and 6-month quit rates; b) cotinine levels; c) cigarettes smoked/day; d) number of quit attempts; and e) nicotine addiction. Process evaluation will compare the two groups on the: a) contacts with intervention; b) medications used; c) helpfulness of the nurse/coach; and d) willingness to recommend the intervention to others.

METHODS/DESIGN

This will be a randomized controlled trial (N = 184). Both interventions will be offered during regularly scheduled safety training at Local 324 Training Center of the International Union of Operating Engineers and both will include optional provision of over-the-counter nicotine replacement therapy and the same number of telephone contacts. However, the Tobacco Tactics website has graphics tailored to Operating Engineers, tailored cessation feedback from the website, and follow up nurse counseling offered by multimedia options including phone and/or email, and/or e-community. Primary Analysis of Aim 1 will be conducted by using logistic regression to compare smoking habits (e.g., quit rates) of those in the intervention arm to those in the control arm. Primary analyses for Aim 2 will compare process measures (e.g., medications used) between the two groups by linear, logistic, and Poisson regression.

DISCUSSION

Dissemination of an efficacious work-site, web-based smoking cessation intervention has the potential to substantially impact cancer rates among this population. Based on the outcome of this smaller study, wider scale testing in conjunction with the International Environment Technology Testing Center which services Operating Engineers across North America (including US, Mexico, and Canada) will be conducted.

TRIAL REGISTRATION

NCT01124110.

A systematic review of the impact of adherence on the effectiveness of e-therapies

Background

As the popularity of e-therapies grows, so too has the body of literature supporting their effectiveness. However, these interventions are often plagued by high attrition rates and varying levels of user adherence. Understanding the role of adherence may be crucial to understanding how program usage influences the effectiveness of e-therapy interventions.

Objective

The aim of this study was to systematically review the e-therapy literature to (1) describe the methods used to assess adherence and (2) evaluate the association of adherence with outcome of these interventions.

Methods

A systematic review of e-therapy interventions was conducted across disease states and behavioral targets. Data were collected on adherence measures, outcomes, and analyses exploring the relationship between adherence measures and outcomes.

Results

Of 69 studies that reported an adherence measure, only 33 (48%) examined the relationship between adherence and outcomes. The number of logins was the most commonly reported measure of adherence, followed by the number of modules completed. The heterogeneity of adherence and outcome measures limited analysis. However, logins appeared to be the measure of adherence most consistently related to outcomes in physical health interventions, while module completion was found to be most related to outcomes in psychological health interventions.

Conclusions

There is large variation in the reporting of adherence and the association of adherence with outcomes. A lack of agreement about how best to measure adherence is likely to contribute to the variation in findings. Physical and psychological outcomes seem influenced by different types of adherence. A composite measure encompassing time online, activity completion, and active engagements with the intervention may be the best measure of adherence. Further research is required to establish a consensus for measuring adherence and to understand the role of adherence in influencing outcomes.